2019
|
| Stein, Charles Michael; Griebler, Dalvan; Danelutto, Marco; Fernandes, Luiz Gustavo Stream Parallelism on the LZSS Data Compression Application for Multi-Cores with GPUs Inproceedings doi In: 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 247-251, IEEE, Pavia, Italy, 2019. @inproceedings{STEIN:LZSS-multigpu:PDP:19,
title = {Stream Parallelism on the LZSS Data Compression Application for Multi-Cores with GPUs},
author = {Charles Michael Stein and Dalvan Griebler and Marco Danelutto and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1109/EMPDP.2019.8671624},
doi = {10.1109/EMPDP.2019.8671624},
year = {2019},
date = {2019-02-01},
booktitle = {27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
pages = {247-251},
publisher = {IEEE},
address = {Pavia, Italy},
series = {PDP'19},
abstract = {GPUs have been used to accelerate different data parallel applications. The challenge consists in using GPUs to accelerate stream processing applications. Our goal is to investigate and evaluate whether stream parallel applications may benefit from parallel execution on both CPU and GPU cores. In this paper, we introduce new parallel algorithms for the Lempel-Ziv-Storer-Szymanski (LZSS) data compression application. We implemented the algorithms targeting both CPUs and GPUs. GPUs have been used with CUDA and OpenCL to exploit inner algorithm data parallelism. Outer stream parallelism has been exploited using CPU cores through SPar. The parallel implementation of LZSS achieved 135 fold speedup using a multi-core CPU and two GPUs. We also observed speedups in applications where we were not expecting to get it using the same combine data-stream parallel exploitation techniques.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
GPUs have been used to accelerate different data parallel applications. The challenge consists in using GPUs to accelerate stream processing applications. Our goal is to investigate and evaluate whether stream parallel applications may benefit from parallel execution on both CPU and GPU cores. In this paper, we introduce new parallel algorithms for the Lempel-Ziv-Storer-Szymanski (LZSS) data compression application. We implemented the algorithms targeting both CPUs and GPUs. GPUs have been used with CUDA and OpenCL to exploit inner algorithm data parallelism. Outer stream parallelism has been exploited using CPU cores through SPar. The parallel implementation of LZSS achieved 135 fold speedup using a multi-core CPU and two GPUs. We also observed speedups in applications where we were not expecting to get it using the same combine data-stream parallel exploitation techniques. |
| Maron, Carlos A. F.; Vogel, Adriano; Griebler, Dalvan; Fernandes, Luiz Gustavo Should PARSEC Benchmarks be More Parametric? A Case Study with Dedup Inproceedings doi In: 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 217-221, IEEE, Pavia, Italy, 2019. @inproceedings{MARON:parametric-parsec:PDP:19,
title = {Should PARSEC Benchmarks be More Parametric? A Case Study with Dedup},
author = {Carlos A. F. Maron and Adriano Vogel and Dalvan Griebler and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1109/EMPDP.2019.8671592},
doi = {10.1109/EMPDP.2019.8671592},
year = {2019},
date = {2019-02-01},
booktitle = {27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
pages = {217-221},
publisher = {IEEE},
address = {Pavia, Italy},
series = {PDP'19},
abstract = {Parallel applications of the same domain can present similar patterns of behavior and characteristics. Characterizing common application behaviors can help for understanding performance aspects in the real-world scenario. One way to better understand and evaluate applications' characteristics is by using customizable/parametric benchmarks that enable users to represent important characteristics at run-time. We observed that parameterization techniques should be better exploited in the available benchmarks, especially on stream processing domain. For instance, although widely used, the stream processing benchmarks available in PARSEC do not support the simulation and evaluation of relevant and modern characteristics. Therefore, our goal is to identify the stream parallelism characteristics present in PARSEC. We also implemented a ready to use parameterization support and evaluated the application behaviors considering relevant performance metrics for stream parallelism (service time, throughput, latency). We choose Dedup to be our case study. The experimental results have shown performance improvements in our parameterization support for Dedup. Moreover, this support increased the customization space for benchmark users, which is simple to use. In the future, our solution can be potentially explored on different parallel architectures and parallel programming frameworks.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Parallel applications of the same domain can present similar patterns of behavior and characteristics. Characterizing common application behaviors can help for understanding performance aspects in the real-world scenario. One way to better understand and evaluate applications' characteristics is by using customizable/parametric benchmarks that enable users to represent important characteristics at run-time. We observed that parameterization techniques should be better exploited in the available benchmarks, especially on stream processing domain. For instance, although widely used, the stream processing benchmarks available in PARSEC do not support the simulation and evaluation of relevant and modern characteristics. Therefore, our goal is to identify the stream parallelism characteristics present in PARSEC. We also implemented a ready to use parameterization support and evaluated the application behaviors considering relevant performance metrics for stream parallelism (service time, throughput, latency). We choose Dedup to be our case study. The experimental results have shown performance improvements in our parameterization support for Dedup. Moreover, this support increased the customization space for benchmark users, which is simple to use. In the future, our solution can be potentially explored on different parallel architectures and parallel programming frameworks. |
| Serpa, Matheus S.; Moreira, Francis B.; Navaux, Philippe O. A.; Cruz, Eduardo H. M.; Diener, Matthias; Griebler, Dalvan; Fernandes, Luiz Gustavo Memory Performance and Bottlenecks in Multicore and GPU Architectures Inproceedings doi In: 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 233-236, IEEE, Pavia, Italy, 2019. @inproceedings{SERPA:memory-gpu-multicore:PDP:19,
title = {Memory Performance and Bottlenecks in Multicore and GPU Architectures},
author = {Matheus S. Serpa and Francis B. Moreira and Philippe O. A. Navaux and Eduardo H. M. Cruz and Matthias Diener and Dalvan Griebler and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1109/EMPDP.2019.8671628},
doi = {10.1109/EMPDP.2019.8671628},
year = {2019},
date = {2019-02-01},
booktitle = {27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
pages = {233-236},
publisher = {IEEE},
address = {Pavia, Italy},
series = {PDP'19},
abstract = {Nowadays, there are several different architectures available not only for the industry, but also for normal consumers. Traditional multicore processors, GPUs, accelerators such as the Sunway SW26010, or even energy efficiency-driven processors such as the ARM family, present very different architectural characteristics. This wide range of characteristics presents a challenge for the developers of applications. Developers must deal with different instruction sets, memory hierarchies, or even different programming paradigms when programming for these architectures. Therefore, the same application can perform well when executing on one architecture, but poorly on another architecture. To optimize an application, it is important to have a deep understanding of how it behaves on different architectures. The related work in this area mostly focuses on a limited analysis encompassing execution time and energy. In this paper, we perform a detailed investigation on the impact of the memory subsystem of different architectures, which is one of the most important aspects to be considered. For this study, we performed experiments in the Broadwell CPU and Pascal GPU, using applications from the Rodinia benchmark suite. In this way, we were able to understand why an application performs well on one architecture and poorly on others.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Nowadays, there are several different architectures available not only for the industry, but also for normal consumers. Traditional multicore processors, GPUs, accelerators such as the Sunway SW26010, or even energy efficiency-driven processors such as the ARM family, present very different architectural characteristics. This wide range of characteristics presents a challenge for the developers of applications. Developers must deal with different instruction sets, memory hierarchies, or even different programming paradigms when programming for these architectures. Therefore, the same application can perform well when executing on one architecture, but poorly on another architecture. To optimize an application, it is important to have a deep understanding of how it behaves on different architectures. The related work in this area mostly focuses on a limited analysis encompassing execution time and energy. In this paper, we perform a detailed investigation on the impact of the memory subsystem of different architectures, which is one of the most important aspects to be considered. For this study, we performed experiments in the Broadwell CPU and Pascal GPU, using applications from the Rodinia benchmark suite. In this way, we were able to understand why an application performs well on one architecture and poorly on others. |
2018
|
| Ewald, Endrius; Vogel, Adriano; Rista, Cassiano; Griebler, Dalvan; Manssour, Isabel; Fernandes, Luiz G. Parallel and Distributed Processing Support for a Geospatial Data Visualization DSL Inproceedings doi In: Symposium on High Performance Computing Systems (WSCAD), pp. 221-228, IEEE, São Paulo, Brazil, 2018. @inproceedings{EWALD:WSCAD:18,
title = {Parallel and Distributed Processing Support for a Geospatial Data Visualization DSL},
author = {Endrius Ewald and Adriano Vogel and Cassiano Rista and Dalvan Griebler and Isabel Manssour and Luiz G. Fernandes},
url = {https://doi.org/10.1109/WSCAD.2018.00042},
doi = {10.1109/WSCAD.2018.00042},
year = {2018},
date = {2018-10-01},
booktitle = {Symposium on High Performance Computing Systems (WSCAD)},
pages = {221-228},
publisher = {IEEE},
address = {São Paulo, Brazil},
abstract = {The amount of data generated worldwide related to geolocalization has exponentially increased. However, the fast processing of this amount of data is a challenge from the programming perspective, and many available solutions require learning a variety of tools and programming languages. This paper introduces the support for parallel and distributed processing in a DSL for Geospatial Data Visualization to speed up the data pre-processing phase. The results have shown the MPI version with dynamic data distribution performing better under medium and large data set files, while MPI-I/O version achieved the best performance with small data set files.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The amount of data generated worldwide related to geolocalization has exponentially increased. However, the fast processing of this amount of data is a challenge from the programming perspective, and many available solutions require learning a variety of tools and programming languages. This paper introduces the support for parallel and distributed processing in a DSL for Geospatial Data Visualization to speed up the data pre-processing phase. The results have shown the MPI version with dynamic data distribution performing better under medium and large data set files, while MPI-I/O version achieved the best performance with small data set files. |
| Maliszewski, Anderson M; Griebler, Dalvan; Vogel, Adriano; Schepke, Claudio On the Performance of Multithreading Applications under Private Cloud Conditions Inproceedings doi In: Symposium on High Performance Computing Systems (WSCAD), pp. 273-273, IEEE, São Paulo, Brazil, 2018. @inproceedings{larcc:multithreading_cloud:WSCAD:18,
title = {On the Performance of Multithreading Applications under Private Cloud Conditions},
author = {Anderson M Maliszewski and Dalvan Griebler and Adriano Vogel and Claudio Schepke},
url = {https://doi.org/10.1109/WSCAD.2018.00055},
doi = {10.1109/WSCAD.2018.00055},
year = {2018},
date = {2018-10-01},
booktitle = {Symposium on High Performance Computing Systems (WSCAD)},
pages = {273-273},
publisher = {IEEE},
address = {São Paulo, Brazil},
abstract = {IaaS private clouds provide an attractive environment for scientific applications. However, the performance is a challenge, as additional abstraction layers imposed by the virtualization can cause overheads and bottlenecks. This paper contributes to a performance analysis of applications with dedicated and shared resources environments under private cloud conditions, deployed with container (LXC) or kernel-based (KVM) instances. We selected five benchmarks from PARSEC suite. In the experimental results, identify a performance pattern of behavior among the applications was hard. For a set of multi-threading applications, the KVM-based cloud instances achieved better performance, however, in the other set of applications, the LXC-based cloud instances performed better.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
IaaS private clouds provide an attractive environment for scientific applications. However, the performance is a challenge, as additional abstraction layers imposed by the virtualization can cause overheads and bottlenecks. This paper contributes to a performance analysis of applications with dedicated and shared resources environments under private cloud conditions, deployed with container (LXC) or kernel-based (KVM) instances. We selected five benchmarks from PARSEC suite. In the experimental results, identify a performance pattern of behavior among the applications was hard. For a set of multi-threading applications, the KVM-based cloud instances achieved better performance, however, in the other set of applications, the LXC-based cloud instances performed better. |
| Griebler, Dalvan; Sensi, Daniele De; Vogel, Adriano; Danelutto, Marco; Fernandes, Luiz Gustavo Service Level Objectives via C++11 Attributes Inproceedings doi In: Euro-Par 2018: Parallel Processing Workshops, pp. 745-756, Springer, Turin, Italy, 2018. @inproceedings{GRIEBLER:SLO-SPar-Nornir:REPARA:18,
title = {Service Level Objectives via C++11 Attributes},
author = {Dalvan Griebler and Daniele De Sensi and Adriano Vogel and Marco Danelutto and Luiz Gustavo Fernandes},
url = {http://dx.doi.org/10.1007/978-3-030-10549-5_58},
doi = {10.1007/978-3-030-10549-5_58},
year = {2018},
date = {2018-08-01},
booktitle = {Euro-Par 2018: Parallel Processing Workshops},
pages = {745-756},
publisher = {Springer},
address = {Turin, Italy},
series = {Lecture Notes in Computer Science},
abstract = {In recent years, increasing attention has been given to the possibility of guaranteeing Service Level Objectives (SLOs) to users about their applications, either regarding performance or power consumption. SLO can be implemented for parallel applications since they can provide many control knobs (e.g., the number of threads to use, the clock frequency of the cores, etc.) to tune the performance and power consumption of the application. Different from most of the existing approaches, we target sequential stream processing applications by proposing a solution based on C++ annotations. The user specifies which parts of the code to parallelize and what type of requirements should be enforced on that part of the code. Our solution first automatically parallelizes the annotated code and then applies self-adaptation approaches at run-time to enforce the user-expressed objectives. We ran experiments on different real-world applications, showing its simplicity and effectiveness.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In recent years, increasing attention has been given to the possibility of guaranteeing Service Level Objectives (SLOs) to users about their applications, either regarding performance or power consumption. SLO can be implemented for parallel applications since they can provide many control knobs (e.g., the number of threads to use, the clock frequency of the cores, etc.) to tune the performance and power consumption of the application. Different from most of the existing approaches, we target sequential stream processing applications by proposing a solution based on C++ annotations. The user specifies which parts of the code to parallelize and what type of requirements should be enforced on that part of the code. Our solution first automatically parallelizes the annotated code and then applies self-adaptation approaches at run-time to enforce the user-expressed objectives. We ran experiments on different real-world applications, showing its simplicity and effectiveness. |
| Vogel, Adriano; Griebler, Dalvan; Sensi, Daniele De; Danelutto, Marco; Fernandes, Luiz Gustavo Autonomic and Latency-Aware Degree of Parallelism Management in SPar Inproceedings doi In: Euro-Par 2018: Parallel Processing Workshops, pp. 28-39, Springer, Turin, Italy, 2018. @inproceedings{VOGEL:Adaptive-Latency-SPar:AutoDaSP:18,
title = {Autonomic and Latency-Aware Degree of Parallelism Management in SPar},
author = {Adriano Vogel and Dalvan Griebler and Daniele De Sensi and Marco Danelutto and Luiz Gustavo Fernandes},
url = {http://dx.doi.org/10.1007/978-3-030-10549-5_3},
doi = {10.1007/978-3-030-10549-5_3},
year = {2018},
date = {2018-08-01},
booktitle = {Euro-Par 2018: Parallel Processing Workshops},
pages = {28-39},
publisher = {Springer},
address = {Turin, Italy},
series = {Lecture Notes in Computer Science},
abstract = {Stream processing applications became a representative workload in current computing systems. A significant part of these applications demands parallelism to increase performance. However, programmers are often facing a trade-off between coding productivity and performance when introducing parallelism. SPar was created for balancing this trade-off to the application programmers by using the C++11 attributes’ annotation mechanism. In SPar and other programming frameworks for stream processing applications, the manual definition of the number of replicas to be used for the stream operators is a challenge. In addition to that, low latency is required by several stream processing applications. We noted that explicit latency requirements are poorly considered on the state-of-the-art parallel programming frameworks. Since there is a direct relationship between the number of replicas and the latency of the application, in this work we propose an autonomic and adaptive strategy to choose the proper number of replicas in SPar to address latency constraints. We experimentally evaluated our implemented strategy and demonstrated its effectiveness on a real-world application, demonstrating that our adaptive strategy can provide higher abstraction levels while automatically managing the latency.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Stream processing applications became a representative workload in current computing systems. A significant part of these applications demands parallelism to increase performance. However, programmers are often facing a trade-off between coding productivity and performance when introducing parallelism. SPar was created for balancing this trade-off to the application programmers by using the C++11 attributes’ annotation mechanism. In SPar and other programming frameworks for stream processing applications, the manual definition of the number of replicas to be used for the stream operators is a challenge. In addition to that, low latency is required by several stream processing applications. We noted that explicit latency requirements are poorly considered on the state-of-the-art parallel programming frameworks. Since there is a direct relationship between the number of replicas and the latency of the application, in this work we propose an autonomic and adaptive strategy to choose the proper number of replicas in SPar to address latency constraints. We experimentally evaluated our implemented strategy and demonstrated its effectiveness on a real-world application, demonstrating that our adaptive strategy can provide higher abstraction levels while automatically managing the latency. |
 | Griebler, Dalvan; Hoffmann, Renato B.; Danelutto, Marco; Fernandes, Luiz Gustavo Stream Parallelism with Ordered Data Constraints on Multi-Core Systems Journal Article doi In: The Journal of Supercomputing, vol. 75, no. 8, pp. 4042-4061, 2018, ISSN: 0920-8542. @article{GRIEBLER:JS:18,
title = {Stream Parallelism with Ordered Data Constraints on Multi-Core Systems},
author = {Dalvan Griebler and Renato B. Hoffmann and Marco Danelutto and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1007/s11227-018-2482-7},
doi = {10.1007/s11227-018-2482-7},
issn = {0920-8542},
year = {2018},
date = {2018-07-01},
urldate = {2018-07-01},
journal = {The Journal of Supercomputing},
volume = {75},
number = {8},
pages = {4042-4061},
publisher = {Springer},
abstract = {It is often a challenge to keep input/output tasks/results in order for parallel computations ver data streams, particularly when stateless task operators are replicated to increase parallelism when there are irregular tasks. Maintaining input/output order requires additional coding effort and may significantly impact the application's actual throughput. Thus, we propose a new implementation technique designed to be easily integrated with any of the existing C++ parallel programming frameworks that support stream parallelism. In this paper, it is first implemented and studied using SPar, our high-level domain-specific language for stream parallelism. We discuss the results of a set of experiments with real-world applications revealing how significant performance improvements may be achieved when our proposed solution is integrated within SPar, especially for data compression applications. Also, we show the results of experiments performed after integrating our solution within FastFlow and TBB, revealing no significant overheads.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
It is often a challenge to keep input/output tasks/results in order for parallel computations ver data streams, particularly when stateless task operators are replicated to increase parallelism when there are irregular tasks. Maintaining input/output order requires additional coding effort and may significantly impact the application's actual throughput. Thus, we propose a new implementation technique designed to be easily integrated with any of the existing C++ parallel programming frameworks that support stream parallelism. In this paper, it is first implemented and studied using SPar, our high-level domain-specific language for stream parallelism. We discuss the results of a set of experiments with real-world applications revealing how significant performance improvements may be achieved when our proposed solution is integrated within SPar, especially for data compression applications. Also, we show the results of experiments performed after integrating our solution within FastFlow and TBB, revealing no significant overheads. |
| Maliszewski, Anderson M; Griebler, Dalvan; Schepke, Claudio; Ditter, Alexander; Fey, Dietmar; Fernandes, Luiz Gustavo The NAS Benchmark Kernels for Single and Multi-Tenant Cloud Instances with LXC/KVM Inproceedings doi In: International Conference on High Performance Computing & Simulation (HPCS), pp. 359-366, IEEE, Orleans, France, 2018. @inproceedings{larcc:NAS_cloud_LXC_KVM:HPCS:2018,
title = {The NAS Benchmark Kernels for Single and Multi-Tenant Cloud Instances with LXC/KVM},
author = {Anderson M Maliszewski and Dalvan Griebler and Claudio Schepke and Alexander Ditter and Dietmar Fey and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1109/HPCS.2018.00066},
doi = {10.1109/HPCS.2018.00066},
year = {2018},
date = {2018-07-01},
booktitle = {International Conference on High Performance Computing & Simulation (HPCS)},
pages = {359-366},
publisher = {IEEE},
address = {Orleans, France},
series = {HPCS'18},
abstract = {Private IaaS clouds are an attractive environment for scientific workloads and applications. It provides advantages such as almost instantaneous availability of high-performance computing in a single node as well as compute clusters, easy access for researchers, and users that do not have access to conventional supercomputers. Furthermore, a cloud infrastructure provides elasticity and scalability to ensure and manage any software dependency on the system with no third-party dependency for researchers. However, one of the biggest challenges is to avoid significant performance degradation when migrating these applications from physical nodes to a cloud environment. Also, we lack more research investigations for multi-tenant cloud instances. In this paper, our goal is to perform a comparative performance evaluation of scientific applications with single and multi-tenancy cloud instances using KVM and LXC virtualization technologies under private cloud conditions. All analyses and evaluations were carried out based on NAS Benchmark kernels to simulate different types of workloads. We applied statistic significance tests to highlight the differences. The results have shown that applications running on LXC-based cloud instances outperform KVM-based cloud instances in 93.75% of the experiments w.r.t single tenant. Regarding multi-tenant, LXC instances outperform KVM instances in 45% of the results, where the performance differences were not as significant as expected.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Private IaaS clouds are an attractive environment for scientific workloads and applications. It provides advantages such as almost instantaneous availability of high-performance computing in a single node as well as compute clusters, easy access for researchers, and users that do not have access to conventional supercomputers. Furthermore, a cloud infrastructure provides elasticity and scalability to ensure and manage any software dependency on the system with no third-party dependency for researchers. However, one of the biggest challenges is to avoid significant performance degradation when migrating these applications from physical nodes to a cloud environment. Also, we lack more research investigations for multi-tenant cloud instances. In this paper, our goal is to perform a comparative performance evaluation of scientific applications with single and multi-tenancy cloud instances using KVM and LXC virtualization technologies under private cloud conditions. All analyses and evaluations were carried out based on NAS Benchmark kernels to simulate different types of workloads. We applied statistic significance tests to highlight the differences. The results have shown that applications running on LXC-based cloud instances outperform KVM-based cloud instances in 93.75% of the experiments w.r.t single tenant. Regarding multi-tenant, LXC instances outperform KVM instances in 45% of the results, where the performance differences were not as significant as expected. |
| Klein, Maikel; Maliszewski, Anderson Mattheus; Griebler, Dalvan Avaliação do Desempenho do Protocolo Bonding em Máquinas Virtuais LXC e KVM Inproceedings In: 15th Escola Regional de Redes de Computadores (ERRC), pp. 1-8, Sociedade Brasileira de Computação, Pelotas, BR, 2018. @inproceedings{larcc:link_agreggation:ERRC:18,
title = {Avaliação do Desempenho do Protocolo Bonding em Máquinas Virtuais LXC e KVM},
author = {Maikel Klein and Anderson Mattheus Maliszewski and Dalvan Griebler},
url = {http://larcc.setrem.com.br/wpcontent/uploads/2018/11/ERRC_2018__Link_Aggregation_.pdf},
year = {2018},
date = {2018-07-01},
booktitle = {15th Escola Regional de Redes de Computadores (ERRC)},
pages = {1-8},
publisher = {Sociedade Brasileira de Computação},
address = {Pelotas, BR},
abstract = {O processamento de grandes volumes de dados (Big Data) e seu armazenamento distribuído vem aumentado gradualmente o uso da rede. Com isso, torna-se necessário o uso de tecnologias para otimizar a largura de banda. Uma das soluções de baixo custo e fácil implementação é a agregação de link. Além disso, a virtualização, usada como base na computação em nuvem, oferece vários benefícios utilizados no Big Data. O objetivo deste trabalho é avaliar o desempenho de rede usando a agregação de link com o protocolo bonding em máquinas virtuais LXC e KVM. Os resultados mostram que o protocolo bonding tem comportamento similar com ambos tipos de virtualização.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
O processamento de grandes volumes de dados (Big Data) e seu armazenamento distribuído vem aumentado gradualmente o uso da rede. Com isso, torna-se necessário o uso de tecnologias para otimizar a largura de banda. Uma das soluções de baixo custo e fácil implementação é a agregação de link. Além disso, a virtualização, usada como base na computação em nuvem, oferece vários benefícios utilizados no Big Data. O objetivo deste trabalho é avaliar o desempenho de rede usando a agregação de link com o protocolo bonding em máquinas virtuais LXC e KVM. Os resultados mostram que o protocolo bonding tem comportamento similar com ambos tipos de virtualização. |
| Griebler, Dalvan; Vogel, Adriano; Maron, Carlos A F; Maliszewski, Anderson M; Schepke, Claudio; Fernandes, Luiz Gustavo Performance of Data Mining, Media, and Financial Applications under Private Cloud Conditions Inproceedings doi In: IEEE Symposium on Computers and Communications (ISCC), pp. 1530-1346, IEEE, Natal, Brazil, 2018. @inproceedings{larcc:parsec_cloudstack_lxc_kvm:ISCC:2018,
title = {Performance of Data Mining, Media, and Financial Applications under Private Cloud Conditions},
author = {Dalvan Griebler and Adriano Vogel and Carlos A F Maron and Anderson M Maliszewski and Claudio Schepke and Luiz Gustavo Fernandes},
url = {https://dx.doi.org/10.1109/ISCC.2018.8538759},
doi = {10.1109/ISCC.2018.8538759},
year = {2018},
date = {2018-06-01},
booktitle = {IEEE Symposium on Computers and Communications (ISCC)},
pages = {1530-1346},
publisher = {IEEE},
address = {Natal, Brazil},
series = {ISCC'18},
abstract = {This paper contributes to a performance analysis of real-world workloads under private cloud conditions. We selected six benchmarks from PARSEC related to three mainstream application domains (financial, data mining, and media processing). Our goal was to evaluate these application domains in different cloud instances and deployment environments, concerning container or kernel-based instances and using dedicated or shared machine resources. Experiments have shown that performance varies according to the application characteristics, virtualization technology, and cloud environment. Results highlighted that financial, data mining, and media processing applications running in the LXC instances tend to outperform KVM when there is a dedicated machine resource environment. However, when two instances are sharing the same machine resources, these applications tend to achieve better performance in the KVM instances. Finally, financial applications achieved better performance in the cloud than media and data mining.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper contributes to a performance analysis of real-world workloads under private cloud conditions. We selected six benchmarks from PARSEC related to three mainstream application domains (financial, data mining, and media processing). Our goal was to evaluate these application domains in different cloud instances and deployment environments, concerning container or kernel-based instances and using dedicated or shared machine resources. Experiments have shown that performance varies according to the application characteristics, virtualization technology, and cloud environment. Results highlighted that financial, data mining, and media processing applications running in the LXC instances tend to outperform KVM when there is a dedicated machine resource environment. However, when two instances are sharing the same machine resources, these applications tend to achieve better performance in the KVM instances. Finally, financial applications achieved better performance in the cloud than media and data mining. |
| Rista, Cassiano; Teixeira, Marcelo; Griebler, Dalvan; Fernandes, Luiz Gustavo Evaluating, Estimating, and Improving Network Performance in Container-based Clouds Inproceedings doi In: IEEE Symposium on Computers and Communications (ISCC), pp. 1530-1346, IEEE, Natal, Brazil, 2018. @inproceedings{larcc:network_performance_container:ISCC:2018,
title = {Evaluating, Estimating, and Improving Network Performance in Container-based Clouds},
author = {Cassiano Rista and Marcelo Teixeira and Dalvan Griebler and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1109/ISCC.2018.8538558},
doi = {10.1109/ISCC.2018.8538558},
year = {2018},
date = {2018-06-01},
booktitle = {IEEE Symposium on Computers and Communications (ISCC)},
pages = {1530-1346},
publisher = {IEEE},
address = {Natal, Brazil},
series = {ISCC'18},
abstract = {Cloud computing has recently attracted a great deal of interest from both industry and academia, emerging as an important paradigm to improve resource utilization, efficiency, flexibility, and pay-per-use. However, cloud platforms inherently include a virtualization layer that imposes performance degradation on network-intensive applications. Thus, it is crucial to anticipate possible performance degradation to resolve system bottlenecks. This paper uses the Petri Nets approach to create different models for evaluating, estimating, and improving network performance in container-based cloud environments. Based on model estimations, we assessed the network bandwidth utilization of the system under different setups. Then, by identifying possible bottlenecks, we show how the system could be modified to improve performance. We then tested how the model would behave through real-world experiments. When the model indicates probable bandwidth saturation, we propose a link aggregation approach to increase bandwidth, using lightweight virtualization to reduce virtualization overhead. Results reveal that our model anticipates the structural and behavioral characteristics of the network in the cloud environment. Therefore, it systematically improves network efficiency, which saves effort, time, and money.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cloud computing has recently attracted a great deal of interest from both industry and academia, emerging as an important paradigm to improve resource utilization, efficiency, flexibility, and pay-per-use. However, cloud platforms inherently include a virtualization layer that imposes performance degradation on network-intensive applications. Thus, it is crucial to anticipate possible performance degradation to resolve system bottlenecks. This paper uses the Petri Nets approach to create different models for evaluating, estimating, and improving network performance in container-based cloud environments. Based on model estimations, we assessed the network bandwidth utilization of the system under different setups. Then, by identifying possible bottlenecks, we show how the system could be modified to improve performance. We then tested how the model would behave through real-world experiments. When the model indicates probable bandwidth saturation, we propose a link aggregation approach to increase bandwidth, using lightweight virtualization to reduce virtualization overhead. Results reveal that our model anticipates the structural and behavioral characteristics of the network in the cloud environment. Therefore, it systematically improves network efficiency, which saves effort, time, and money. |
 | Rockenbach, Dinei A.; Anderle, Nadine; Griebler, Dalvan; Souza, Samuel Estudo Comparativo de Bancos de Dados NoSQL Journal Article doi In: Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC), vol. 1, no. 8, 2018. @article{larcc:comparativo_nosql:REABTIC:18,
title = {Estudo Comparativo de Bancos de Dados NoSQL},
author = {Dinei A. Rockenbach and Nadine Anderle and Dalvan Griebler and Samuel Souza},
url = {https://revistas.setrem.com.br/index.php/reabtic/article/view/286},
doi = {10.5281/zenodo.1228503},
year = {2018},
date = {2018-04-01},
journal = {Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC)},
volume = {1},
number = {8},
publisher = {SETREM},
address = {Três de Maio, RS, Brazil},
abstract = {NoSQL databases emerged to fill limitations of the relational databases. The many options for each one of the categories, and their distinct characteristics and focus makes this assessment very difficult for decision makers. Most of the time, decisions are taken without the attention and background deserved due to the related complexities. This article aims to compare the relevant characteristics of each database, abstracting the information that bases the market marketing of them. We concluded that although the databases are labeled in a specific category, there is a significant disparity in the functionalities offered by each of them. Also, we observed that new databases are emerging even though there are well-established databases in each one of the categories studied. Finally, it is very challenging to suggest the best database for each category because each scenario has its requirements, which requires a careful analysis where our work can help to simplify this kind of decision.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
NoSQL databases emerged to fill limitations of the relational databases. The many options for each one of the categories, and their distinct characteristics and focus makes this assessment very difficult for decision makers. Most of the time, decisions are taken without the attention and background deserved due to the related complexities. This article aims to compare the relevant characteristics of each database, abstracting the information that bases the market marketing of them. We concluded that although the databases are labeled in a specific category, there is a significant disparity in the functionalities offered by each of them. Also, we observed that new databases are emerging even though there are well-established databases in each one of the categories studied. Finally, it is very challenging to suggest the best database for each category because each scenario has its requirements, which requires a careful analysis where our work can help to simplify this kind of decision. |
| Stein, Charles M.; Griebler, Dalvan Explorando o Paralelismo de Stream em CPU e de Dados em GPU na Aplicação de Filtro Sobel Inproceedings In: 18th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS), pp. 137-140, Sociedade Brasileira de Computação, Porto Alegre, RS, Brazil, 2018. @inproceedings{larcc:stream_gpu_cuda:ERAD:18,
title = {Explorando o Paralelismo de Stream em CPU e de Dados em GPU na Aplicação de Filtro Sobel},
author = {Charles M. Stein and Dalvan Griebler},
url = {http://larcc.setrem.com.br/wp-content/uploads/2018/04/LARCC_ERAD_IC_Stein_2018.pdf},
year = {2018},
date = {2018-04-01},
booktitle = {18th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS)},
pages = {137-140},
publisher = {Sociedade Brasileira de Computação},
address = {Porto Alegre, RS, Brazil},
abstract = {O objetivo deste estudo é a paralelização combinada do stream em CPU e dos dados em GPU usando uma aplicação de filtro sobel. Foi realizada uma avaliação do desempenho de OpenCL, OpenACC e CUDA com o algorí-timo de multiplicação de matrizes para escolha da ferramenta a ser usada com a SPar. Concluiu-se que apesar da GPU apresentar um speedup de 11.81x com CUDA, o uso exclusivo da CPU com a SPar é mais vantajoso nesta aplicação.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
O objetivo deste estudo é a paralelização combinada do stream em CPU e dos dados em GPU usando uma aplicação de filtro sobel. Foi realizada uma avaliação do desempenho de OpenCL, OpenACC e CUDA com o algorí-timo de multiplicação de matrizes para escolha da ferramenta a ser usada com a SPar. Concluiu-se que apesar da GPU apresentar um speedup de 11.81x com CUDA, o uso exclusivo da CPU com a SPar é mais vantajoso nesta aplicação. |
| Maliszewski, Anderson M.; Griebler, Dalvan; Schepke, Claudio Desempenho em Instâncias LXC e KVM de Nuvem Privada usando Aplicações Científicas Inproceedings In: 18th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS), pp. 129-132, Sociedade Brasileira de Computação, Porto Alegre, RS, Brazil, 2018. @inproceedings{larcc:cloudtack_lxc_kvm:ERAD:18,
title = {Desempenho em Instâncias LXC e KVM de Nuvem Privada usando Aplicações Científicas},
author = {Anderson M. Maliszewski and Dalvan Griebler and Claudio Schepke},
url = {http://larcc.setrem.com.br/wp-content/uploads/2018/04/LARCC_ERAD_IC_MAliszweski_2018.pdf},
year = {2018},
date = {2018-04-01},
booktitle = {18th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS)},
pages = {129-132},
publisher = {Sociedade Brasileira de Computação},
address = {Porto Alegre, RS, Brazil},
abstract = {As nuvens privadas IaaS oferecem um ambiente atraente para aplicações científicas. Como este ambiente possui camadas adicionais de abstração, alcançar um bom desempenho é um desafio. O objetivo é realizar uma avaliação de desempenho das tecnologias de virtualização baseadas em KVM e LXC gerenciadas pelo CloudStack, usando benchmarks da suite NPB-OMP. Os resultados revelaram que LXC supera KVM em 93,75% dos experimentos.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
As nuvens privadas IaaS oferecem um ambiente atraente para aplicações científicas. Como este ambiente possui camadas adicionais de abstração, alcançar um bom desempenho é um desafio. O objetivo é realizar uma avaliação de desempenho das tecnologias de virtualização baseadas em KVM e LXC gerenciadas pelo CloudStack, usando benchmarks da suite NPB-OMP. Os resultados revelaram que LXC supera KVM em 93,75% dos experimentos. |
| Hoffmann, Renato B.; Griebler, Dalvan; Fernandes, Luiz G. Paralelização de uma Aplicação de Detecção e Eliminação de Ruídos em Streaming de Vídeo com a DSL SPar Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 2, Sociedade Brasileira de Computação (SBC), Porto Alegre, BR, 2018. @inproceedings{HOFFMANN:ERAD:18,
title = {Paralelização de uma Aplicação de Detecção e Eliminação de Ruídos em Streaming de Vídeo com a DSL SPar},
author = {Renato B. Hoffmann and Dalvan Griebler and Luiz G. Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2018/CR_ERAD_IC_Hoffmann_2018.pdf},
year = {2018},
date = {2018-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {2},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {Porto Alegre, BR},
abstract = {Restauração de imagem é uma importante etapa de qualquer sistema de computação gráfica. Este trabalho tem como objetivo apresentar e avaliar o paralelismo de Denoiser, uma aplicação para detecção e eliminação de ruído em streaming de vídeo. Foram avaliados o speed-up e programabilidade das interfaces SPar, Thread Building Blocks e FastFlow. Os resultados mostram que a SPar obteve bons resultados de programabilidade e desempenho.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Restauração de imagem é uma importante etapa de qualquer sistema de computação gráfica. Este trabalho tem como objetivo apresentar e avaliar o paralelismo de Denoiser, uma aplicação para detecção e eliminação de ruído em streaming de vídeo. Foram avaliados o speed-up e programabilidade das interfaces SPar, Thread Building Blocks e FastFlow. Os resultados mostram que a SPar obteve bons resultados de programabilidade e desempenho. |
| Loff, Junior; Griebler, Dalvan; Sandes, Edans; Melo, Alba; Fernandes, Luiz G. Suporte ao Paralelismo Multi-Core com FastFlow e TBB em uma Aplicação de Alinhamento de Sequências de DNA Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 2, Sociedade Brasileira de Computação (SBC), Porto Alegre, BR, 2018. @inproceedings{LOFF:ERAD:18,
title = {Suporte ao Paralelismo Multi-Core com FastFlow e TBB em uma Aplicação de Alinhamento de Sequências de DNA},
author = {Junior Loff and Dalvan Griebler and Edans Sandes and Alba Melo and Luiz G. Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2018/CR_ERAD_IC_Loff_2018.pdf},
year = {2018},
date = {2018-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {2},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {Porto Alegre, BR},
abstract = {Quando uma sequência biológica é obtida, é comum alinhá-la com outra já estudada para determinar suas características. O desafio é processar este alinhamento em tempo útil. Neste trabalho exploramos o paralelismo em uma aplicação de alinhamento de sequências de DNA utilizando as bibliotecas FastFlow e Intel TBB. Os experimentos mostram que a versão TBB obteve até 4% melhor tempo de execução em comparação à versão original em OpenMP.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Quando uma sequência biológica é obtida, é comum alinhá-la com outra já estudada para determinar suas características. O desafio é processar este alinhamento em tempo útil. Neste trabalho exploramos o paralelismo em uma aplicação de alinhamento de sequências de DNA utilizando as bibliotecas FastFlow e Intel TBB. Os experimentos mostram que a versão TBB obteve até 4% melhor tempo de execução em comparação à versão original em OpenMP. |
| Griebler, Dalvan; Loff, Junior; Mencagli, Gabriele; Danelutto, Marco; Fernandes, Luiz Gustavo Efficient NAS Benchmark Kernels with C++ Parallel Programming Inproceedings doi In: 26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 733-740, IEEE, Cambridge, UK, 2018. @inproceedings{GRIEBLER:NAS-CPP:PDP:18,
title = {Efficient NAS Benchmark Kernels with C++ Parallel Programming},
author = {Dalvan Griebler and Junior Loff and Gabriele Mencagli and Marco Danelutto and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1109/PDP2018.2018.00120},
doi = {10.1109/PDP2018.2018.00120},
year = {2018},
date = {2018-03-01},
booktitle = {26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
pages = {733-740},
publisher = {IEEE},
address = {Cambridge, UK},
series = {PDP'18},
abstract = {Benchmarking is a way to study the performance of new architectures and parallel programming frameworks. Well-established benchmark suites such as the NAS Parallel Benchmarks (NPB) comprise legacy codes that still lack portability to C++ language. As a consequence, a set of high-level and easy-to-use C++ parallel programming frameworks cannot be tested in NPB. Our goal is to describe a C++ porting of the NPB kernels and to analyze the performance achieved by different parallel implementations written using the Intel TBB, OpenMP and FastFlow frameworks for Multi-Cores. The experiments show an efficient code porting from Fortran to C++ and an efficient parallelization on average.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Benchmarking is a way to study the performance of new architectures and parallel programming frameworks. Well-established benchmark suites such as the NAS Parallel Benchmarks (NPB) comprise legacy codes that still lack portability to C++ language. As a consequence, a set of high-level and easy-to-use C++ parallel programming frameworks cannot be tested in NPB. Our goal is to describe a C++ porting of the NPB kernels and to analyze the performance achieved by different parallel implementations written using the Intel TBB, OpenMP and FastFlow frameworks for Multi-Cores. The experiments show an efficient code porting from Fortran to C++ and an efficient parallelization on average. |
 | Griebler, Dalvan; Hoffmann, Renato B.; Danelutto, Marco; Fernandes, Luiz Gustavo High-Level and Productive Stream Parallelism for Dedup, Ferret, and Bzip2 Journal Article doi In: International Journal of Parallel Programming, vol. 47, no. 1, pp. 253-271, 2018, ISSN: 1573-7640. @article{GRIEBLER:IJPP:18,
title = {High-Level and Productive Stream Parallelism for Dedup, Ferret, and Bzip2},
author = {Dalvan Griebler and Renato B. Hoffmann and Marco Danelutto and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1007/s10766-018-0558-x},
doi = {10.1007/s10766-018-0558-x},
issn = {1573-7640},
year = {2018},
date = {2018-02-01},
journal = {International Journal of Parallel Programming},
volume = {47},
number = {1},
pages = {253-271},
publisher = {Springer},
abstract = {Parallel programming has been a challenging task for application programmers. Stream processing is an application domain present in several scientific, enterprise, and financial areas that lack suitable abstractions to exploit parallelism. Our goal is to assess the feasibility of state-of-the-art frameworks/libraries (Pthreads, TBB, and FastFlow) and the SPar domain-specific language for real-world streaming applications (Dedup, Ferret, and Bzip2) targeting multi-core architectures. SPar was specially designed to provide high-level and productive stream parallelism abstractions, supporting programmers with standard C++-11 annotations. For the experiments, we implemented three streaming applications. We discussed SPar’s programmability advantages compared to the frameworks in terms of productivity and structured parallel programming. The results demonstrate that SPar improves productivity and provides the necessary features to achieve similar performances compared to the state-of-the-art.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Parallel programming has been a challenging task for application programmers. Stream processing is an application domain present in several scientific, enterprise, and financial areas that lack suitable abstractions to exploit parallelism. Our goal is to assess the feasibility of state-of-the-art frameworks/libraries (Pthreads, TBB, and FastFlow) and the SPar domain-specific language for real-world streaming applications (Dedup, Ferret, and Bzip2) targeting multi-core architectures. SPar was specially designed to provide high-level and productive stream parallelism abstractions, supporting programmers with standard C++-11 annotations. For the experiments, we implemented three streaming applications. We discussed SPar’s programmability advantages compared to the frameworks in terms of productivity and structured parallel programming. The results demonstrate that SPar improves productivity and provides the necessary features to achieve similar performances compared to the state-of-the-art. |
2017
|
| Griebler, Dalvan; Hoffmann, Renato B.; Loff, Junior; Danelutto, Marco; Fernandes, Luiz G. High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications Inproceedings In: XVIII Simpósio em Sistemas Computacionais de Alto Desempenho, pp. 16-27, SBC, Campinas, SP, Brasil, 2017. @inproceedings{GRIEBLER:WSCAD:17,
title = {High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications},
author = {Dalvan Griebler and Renato B. Hoffmann and Junior Loff and Marco Danelutto and Luiz G. Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2017/CR_WSCAD_2017.pdf},
year = {2017},
date = {2017-10-01},
booktitle = {XVIII Simpósio em Sistemas Computacionais de Alto Desempenho},
pages = {16-27},
publisher = {SBC},
address = {Campinas, SP, Brasil},
abstract = {The stream processing domain is present in several real-world applications that are running on multi-core systems. In this paper, we focus on data compression applications that are an important sub-set of this domain. Our main goal is to assess the programmability and efficiency of domain-specific language called SPar. It was specially designed for expressing stream parallelism and it promises higher-level parallelism abstractions without significant performance losses. Therefore, we parallelized Lzip and Bzip2 compressors with SPar and compared with state-of-the-art frameworks. The results revealed that SPar is able to efficiently exploit stream parallelism as well as provide suitable abstractions with less code intrusion and code re-factoring.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The stream processing domain is present in several real-world applications that are running on multi-core systems. In this paper, we focus on data compression applications that are an important sub-set of this domain. Our main goal is to assess the programmability and efficiency of domain-specific language called SPar. It was specially designed for expressing stream parallelism and it promises higher-level parallelism abstractions without significant performance losses. Therefore, we parallelized Lzip and Bzip2 compressors with SPar and compared with state-of-the-art frameworks. The results revealed that SPar is able to efficiently exploit stream parallelism as well as provide suitable abstractions with less code intrusion and code re-factoring. |
| Griebler, Dalvan; Fernandes, Luiz Gustavo Towards Distributed Parallel Programming Support for the SPar DSL Inproceedings doi In: Parallel Computing is Everywhere, Proceedings of the International
Conference on Parallel Computing, pp. 563-572, IOS Press, Bologna, Italy, 2017. @inproceedings{GRIEBLER:PARCO:17,
title = {Towards Distributed Parallel Programming Support for the SPar DSL},
author = {Dalvan Griebler and Luiz Gustavo Fernandes},
url = {https://doi.org/10.3233/978-1-61499-843-3-563},
doi = {10.3233/978-1-61499-843-3-563},
year = {2017},
date = {2017-09-01},
booktitle = {Parallel Computing is Everywhere, Proceedings of the International
Conference on Parallel Computing},
pages = {563-572},
publisher = {IOS Press},
address = {Bologna, Italy},
series = {ParCo'17},
abstract = {SPar was originally designed to provide high-level abstractions for stream parallelism in C++ programs targeting multi-core systems. This work proposes distributed parallel programming support for SPar targeting cluster environments. The goal is to preserve the original semantics while source-to-source code transformations will be turned into MPI (Message Passing Interface) parallel code. The results of the experiments presented in the paper demonstrate improved programmability without significant performance losses.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
SPar was originally designed to provide high-level abstractions for stream parallelism in C++ programs targeting multi-core systems. This work proposes distributed parallel programming support for SPar targeting cluster environments. The goal is to preserve the original semantics while source-to-source code transformations will be turned into MPI (Message Passing Interface) parallel code. The results of the experiments presented in the paper demonstrate improved programmability without significant performance losses. |
| Griebler, Dalvan; Hoffmann, Renato B.; Danelutto, Marco; Fernandes, Luiz Gustavo Higher-Level Parallelism Abstractions for Video Applications with SPar Inproceedings doi In: Parallel Computing is Everywhere, Proceedings of the International Conference on Parallel Computing, pp. 698-707, IOS Press, Bologna, Italy, 2017. @inproceedings{GRIEBLER:REPARA:17,
title = {Higher-Level Parallelism Abstractions for Video Applications with SPar},
author = {Dalvan Griebler and Renato B. Hoffmann and Marco Danelutto and Luiz Gustavo Fernandes},
url = {https://doi.org/10.3233/978-1-61499-843-3-698},
doi = {10.3233/978-1-61499-843-3-698},
year = {2017},
date = {2017-09-01},
booktitle = {Parallel Computing is Everywhere, Proceedings of the International Conference on Parallel Computing},
pages = {698-707},
publisher = {IOS Press},
address = {Bologna, Italy},
series = {ParCo'17},
abstract = {SPar is a Domain-Specific Language (DSL) designed to provide high-level parallel programming abstractions for streaming applications. Video processing application domain requires parallel processing to extract and analyze information quickly. When using state-of-the-art frameworks such as FastFlow and TBB, the application programmer has to manage source code re-factoring and performance optimization to implement parallelism efficiently. Our goal is to make this process easier for programmers through SPar. Thus we assess SPar's programming language and its performance in traditional video applications. We also discuss different implementations compared to the ones of SPar. Results demonstrate that SPar maintains the sequential code structure, is less code intrusive, and provides higher-level programming abstractions without introducing notable performance losses. Therefore, it represents a good choice for application programmers from the video processing domain.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
SPar is a Domain-Specific Language (DSL) designed to provide high-level parallel programming abstractions for streaming applications. Video processing application domain requires parallel processing to extract and analyze information quickly. When using state-of-the-art frameworks such as FastFlow and TBB, the application programmer has to manage source code re-factoring and performance optimization to implement parallelism efficiently. Our goal is to make this process easier for programmers through SPar. Thus we assess SPar's programming language and its performance in traditional video applications. We also discuss different implementations compared to the ones of SPar. Results demonstrate that SPar maintains the sequential code structure, is less code intrusive, and provides higher-level programming abstractions without introducing notable performance losses. Therefore, it represents a good choice for application programmers from the video processing domain. |
| Leiria, Raul; Vogel, Adriano; Griebler, Dalvan; Schepke, Claudio Uma Proposta para o Monitoramento Energético de Nuvens Computacionais Privadas no Zabbix Inproceedings In: 15th Escola Regional de Redes de Computadores (ERRC), pp. 1-4, Sociedade Brasileira de Computação, Santa Maria, BR, 2017. @inproceedings{larcc:zabbix_energy_cloud:ERRC:17,
title = {Uma Proposta para o Monitoramento Energético de Nuvens Computacionais Privadas no Zabbix},
author = {Raul Leiria and Adriano Vogel and Dalvan Griebler and Claudio Schepke},
url = {http://larcc.setrem.com.br/wp-content/uploads/2018/02/CR_ERRC_Leiria_2017.pdf},
year = {2017},
date = {2017-09-01},
booktitle = {15th Escola Regional de Redes de Computadores (ERRC)},
pages = {1-4},
publisher = {Sociedade Brasileira de Computação},
address = {Santa Maria, BR},
abstract = {In the last years, cloud computing has been consolidated as a new computational paradigm due to its widespread adoption. Proportionally, this leverages to the increasing of the power consumption by data centers. As a consequence, there is a witnessed about the growing demand for monitoring the power consumption on computational infrastructures. Therefore, in this work is proposed a mechanism to monitor the cloud computing power draw through the Zabbix open-source networking monitoring tool.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In the last years, cloud computing has been consolidated as a new computational paradigm due to its widespread adoption. Proportionally, this leverages to the increasing of the power consumption by data centers. As a consequence, there is a witnessed about the growing demand for monitoring the power consumption on computational infrastructures. Therefore, in this work is proposed a mechanism to monitor the cloud computing power draw through the Zabbix open-source networking monitoring tool. |
| Ledur, Cleverson; Griebler, Dalvan; Manssour, Isabel; Fernandes, Luiz Gustavo A High-Level DSL for Geospatial Visualizations with Multi-core Parallelism Support Inproceedings doi In: 41th IEEE Computer Society Signature Conference on Computers, Software and Applications, pp. 298-304, IEEE, Torino, Italy, 2017. @inproceedings{LEDUR:COMPSAC:17,
title = {A High-Level DSL for Geospatial Visualizations with Multi-core Parallelism Support},
author = {Cleverson Ledur and Dalvan Griebler and Isabel Manssour and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1109/COMPSAC.2017.18},
doi = {10.1109/COMPSAC.2017.18},
year = {2017},
date = {2017-07-01},
booktitle = {41th IEEE Computer Society Signature Conference on Computers, Software and Applications},
pages = {298-304},
publisher = {IEEE},
address = {Torino, Italy},
series = {COMPSAC'17},
abstract = {The amount of data generated worldwide associated with geolocalization has exponentially increased over the last decade due to social networks, population demographics, and the popularization of Global Positioning Systems. Several methods for geovisualization have already been developed, but many of them are focused on a specific application or require learning a variety of tools and programming languages. It becomes even more difficult when users have to manage a large amount of data because state-of-the-art alternatives require the use of third-party pre-processing tools. We present a novel Domain-Specific Language (DSL), which focuses on large data geovisualizations. Through a compiler, we support automatic visualization generations and data pre-processing. The system takes advantage of multi-core parallelism to speed-up data pre-processing abstractly. Our experiments were designated to highlight the programming effort and performance of our DSL. The results have shown a considerable programming effort reduction and efficient parallelism support with respect to the sequential version.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The amount of data generated worldwide associated with geolocalization has exponentially increased over the last decade due to social networks, population demographics, and the popularization of Global Positioning Systems. Several methods for geovisualization have already been developed, but many of them are focused on a specific application or require learning a variety of tools and programming languages. It becomes even more difficult when users have to manage a large amount of data because state-of-the-art alternatives require the use of third-party pre-processing tools. We present a novel Domain-Specific Language (DSL), which focuses on large data geovisualizations. Through a compiler, we support automatic visualization generations and data pre-processing. The system takes advantage of multi-core parallelism to speed-up data pre-processing abstractly. Our experiments were designated to highlight the programming effort and performance of our DSL. The results have shown a considerable programming effort reduction and efficient parallelism support with respect to the sequential version. |
| Rista, Cassiano; Griebler, Dalvan; Maron, Carlos A. F.; Fernandes, Luiz Gustavo Improving the Network Performance of a Container-Based Cloud Environment for Hadoop Systems Inproceedings doi In: International Conference on High Performance Computing & Simulation (HPCS), pp. 619-626, IEEE, Genoa, Italy, 2017. @inproceedings{larcc:link_aggregation:HPCS:2017,
title = {Improving the Network Performance of a Container-Based Cloud Environment for Hadoop Systems},
author = {Cassiano Rista and Dalvan Griebler and Carlos A. F. Maron and Luiz Gustavo Fernandes},
url = {http://ieeexplore.ieee.org/document/8035136/},
doi = {10.1109/HPCS.2017.97},
year = {2017},
date = {2017-07-01},
booktitle = {International Conference on High Performance Computing & Simulation (HPCS)},
pages = {619-626},
publisher = {IEEE},
address = {Genoa, Italy},
series = {HPCS'17},
abstract = {Cloud computing has emerged as an important paradigm to improve resource utilization, efficiency, flexibility, and the pay-per-use billing structure. However, cloud platforms cause performance degradations due to their virtualization layer and may not be appropriate for the requirements of high-performance applications, such as big data. This paper tackles the problem of improving network performance in container-based cloud instances to create a viable alternative to run network intensive Hadoop applications. Our approach consists of deploying link aggregation via the IEEE 802.3ad standard to increase the available bandwidth and using LXC (Linux Container) cloud instances to create a Hadoop cluster. In order to evaluate the efficiency of our approach and the overhead added by the container-based cloud environment, we ran a set of experiments to measure throughput, latency, bandwidth utilization, and completion times. The results prove that our approach adds minimal overhead in cloud environment as well as increases throughput and reduces latency. Moreover, our approach demonstrates a suitable alternative for running Hadoop applications, reducing completion times up to 33.73%},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cloud computing has emerged as an important paradigm to improve resource utilization, efficiency, flexibility, and the pay-per-use billing structure. However, cloud platforms cause performance degradations due to their virtualization layer and may not be appropriate for the requirements of high-performance applications, such as big data. This paper tackles the problem of improving network performance in container-based cloud instances to create a viable alternative to run network intensive Hadoop applications. Our approach consists of deploying link aggregation via the IEEE 802.3ad standard to increase the available bandwidth and using LXC (Linux Container) cloud instances to create a Hadoop cluster. In order to evaluate the efficiency of our approach and the overhead added by the container-based cloud environment, we ran a set of experiments to measure throughput, latency, bandwidth utilization, and completion times. The results prove that our approach adds minimal overhead in cloud environment as well as increases throughput and reduces latency. Moreover, our approach demonstrates a suitable alternative for running Hadoop applications, reducing completion times up to 33.73% |
| Rockenbach, Dinei A.; Anderle, Nadine; Griebler, Dalvan; Souza, Samuel Estudo Comparativo de Banco de Dados Chave-Valor com Armazenamento em Memória Inproceedings In: 13th Escola Regional de Banco de Dados (ERBD), pp. 1-4, Sociedade Brasileira de Computação, Passo Fundo, BR, 2017. @inproceedings{larcc:database_keyvalue:ERBD:17,
title = {Estudo Comparativo de Banco de Dados Chave-Valor com Armazenamento em Memória},
author = {Dinei A. Rockenbach and Nadine Anderle and Dalvan Griebler and Samuel Souza},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/03/ANDERLE_ERBD_2017.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {13th Escola Regional de Banco de Dados (ERBD)},
pages = {1-4},
publisher = {Sociedade Brasileira de Computação},
address = {Passo Fundo, BR},
abstract = {Key-value databases emerge to address relational databases' limitations and with the increasing capacity of RAM memory it is possible to offer greater performance and versatility in data storage and processing. The objective is to perform a comparative study of key-value databases with memory storage Redis, Memcached, Voldemort, Aerospike, Hazelcast and Riak KV. Thus, the work contributed to an analysis of different databases and with results that qualitatively demonstrated the characteristics and pointed out the main advantages.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Key-value databases emerge to address relational databases' limitations and with the increasing capacity of RAM memory it is possible to offer greater performance and versatility in data storage and processing. The objective is to perform a comparative study of key-value databases with memory storage Redis, Memcached, Voldemort, Aerospike, Hazelcast and Riak KV. Thus, the work contributed to an analysis of different databases and with results that qualitatively demonstrated the characteristics and pointed out the main advantages. |
| Araujo, Gabriell; Ledur, Cleverson; Griebler, Dalvan; Fernandes, Luiz G. Exploração do Paralelismo em Algoritmos de Mineração de Dados com Pthreads, OpenMP, FastFlow, TBB e Phoenix++ Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 4, Sociedade Brasileira de Computação (SBC), Ijuí, RS, BR, 2017. @inproceedings{ARAUJO:ERAD:17,
title = {Exploração do Paralelismo em Algoritmos de Mineração de Dados com Pthreads, OpenMP, FastFlow, TBB e Phoenix++},
author = {Gabriell Araujo and Cleverson Ledur and Dalvan Griebler and Luiz G. Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2017/CR_ERAD_IC_Araujo_2017.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {4},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {Ijuí, RS, BR},
abstract = {Com o objetivo de introduzir algoritmos de mineração de dados paralelos na DSL GMaVis, foram paralelizadas quatro aplicações com cinco interfaces de programação paralela. Este trabalho apresenta a comparação destas interfaces, a fim de avaliar qual oferece maior desempenho e produtividade de código. Os resultados demonstram que é possível atingir menor número de linhas de código e bom desempenho com OpenMP e FastFlow.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Com o objetivo de introduzir algoritmos de mineração de dados paralelos na DSL GMaVis, foram paralelizadas quatro aplicações com cinco interfaces de programação paralela. Este trabalho apresenta a comparação destas interfaces, a fim de avaliar qual oferece maior desempenho e produtividade de código. Os resultados demonstram que é possível atingir menor número de linhas de código e bom desempenho com OpenMP e FastFlow. |
| Baum, Willian; Maron, Carlos A. F.; Griebler, Dalvan; Schepke, Claudio Caracterização do Desempenho de Aplicações Pipeline em Instâncias KVM e LXC de uma Nuvem CloudStack Inproceedings In: 17th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS), pp. 267-270, Sociedade Brasileira de Computação, Ijuí, RS, Brazil, 2017. @inproceedings{hiperfcloud:parsec_pipeline:ERAD:17,
title = {Caracterização do Desempenho de Aplicações Pipeline em Instâncias KVM e LXC de uma Nuvem CloudStack},
author = {Willian Baum and Carlos A. F. Maron and Dalvan Griebler and Claudio Schepke},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/03/BAUM_ERAD_2017.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {17th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS)},
pages = {267-270},
publisher = {Sociedade Brasileira de Computação},
address = {Ijuí, RS, Brazil},
abstract = {Nuvens computacionais são uma alternativa para a computação de alto desempenho. Este artigo avalia o desempenho de aplicações estruturadas com o padrão pipeline em uma implantação de nuvem CloudStack com instâncias do tipo LXC e KVM. Foram testadas as aplicações Ferret e Dedup da suíte PARSEC, bem como constatado uma diferença significativa no Dedup. Na média geral, para esta aplicação a instância LXC é 40,19% melhor que a KVM.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Nuvens computacionais são uma alternativa para a computação de alto desempenho. Este artigo avalia o desempenho de aplicações estruturadas com o padrão pipeline em uma implantação de nuvem CloudStack com instâncias do tipo LXC e KVM. Foram testadas as aplicações Ferret e Dedup da suíte PARSEC, bem como constatado uma diferença significativa no Dedup. Na média geral, para esta aplicação a instância LXC é 40,19% melhor que a KVM. |
| Löff, Júnior; Griebler, Dalvan; Ledur, Cleverson; Fernandes, Luiz G. Explorando a Flexibilidade e o Desempenho da Biblioteca FastFlow com o Padrão Paralelo Farm Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 4, Sociedade Brasileira de Computação (SBC), Ijuí, RS, BR, 2017. @inproceedings{LOFF:ERAD:17,
title = {Explorando a Flexibilidade e o Desempenho da Biblioteca FastFlow com o Padrão Paralelo Farm},
author = {Júnior Löff and Dalvan Griebler and Cleverson Ledur and Luiz G. Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2017/CR_ERAD_IC_Loff_2017.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {4},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {Ijuí, RS, BR},
abstract = {O paralelismo é uma tarefa para especialistas, onde o desafio é utilizar abstrações que ofereçam a flexibilidade e expressividade necessária para atingir o melhor desempenho. Este artigo visa explorar variações na implementação do padrão Farm utilizando a biblioteca FastFlow nos algoritmos K-means (domínio da mineração de dados) e Mandelbrot Set (domínio da matemática). Concluímos que o padrão Farm oferece boa flexibilidade e bom desempenho.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
O paralelismo é uma tarefa para especialistas, onde o desafio é utilizar abstrações que ofereçam a flexibilidade e expressividade necessária para atingir o melhor desempenho. Este artigo visa explorar variações na implementação do padrão Farm utilizando a biblioteca FastFlow nos algoritmos K-means (domínio da mineração de dados) e Mandelbrot Set (domínio da matemática). Concluímos que o padrão Farm oferece boa flexibilidade e bom desempenho. |
| Vogel, Adriano; Griebler, Dalvan; Fernandes, Luiz Gustavo Proposta de Implementação de Grau de Paralelismo Adaptativo em uma DSL para Paralelismo de Stream Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 4, Sociedade Brasileira de Computação (SBC), Ijuí, RS, BR, 2017. @inproceedings{VOGEL:ERAD:17,
title = {Proposta de Implementação de Grau de Paralelismo Adaptativo em uma DSL para Paralelismo de Stream},
author = {Adriano Vogel and Dalvan Griebler and Luiz Gustavo Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2017/CR_ERAD_PG_Vogel_2017.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {4},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {Ijuí, RS, BR},
abstract = {A classe de aplicações de stream possuem características únicas, como variação nas entradas/saídas e execuções por períodos indefinidos. Este paradigma é utilizado com intuito de diminuir os tempos de execução e aumentar a vazão das aplicações. Nesse estudo é proposto o suporte adaptativo do grau de paralelismo de stream na DSL (Domain-Specific Language) SPar.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
A classe de aplicações de stream possuem características únicas, como variação nas entradas/saídas e execuções por períodos indefinidos. Este paradigma é utilizado com intuito de diminuir os tempos de execução e aumentar a vazão das aplicações. Nesse estudo é proposto o suporte adaptativo do grau de paralelismo de stream na DSL (Domain-Specific Language) SPar. |
| Maliszewski, Anderson M.; Vogel, Adriano; Griebler, Dalvan; Schepke, Claudio Desempenho das Operações de Criar e Deletar Instâncias KVM Simultâneas em Nuvens CloudStack e OpenStack Inproceedings In: 17th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS), pp. 283-286, Sociedade Brasileira de Computação, Ijuí, RS, Brazil, 2017. @inproceedings{hiperfcloud:management_operations:ERAD:17,
title = {Desempenho das Operações de Criar e Deletar Instâncias KVM Simultâneas em Nuvens CloudStack e OpenStack},
author = {Anderson M. Maliszewski and Adriano Vogel and Dalvan Griebler and Claudio Schepke},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/03/MALISZEWSKI_ERAD_2017.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {17th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS)},
pages = {283-286},
publisher = {Sociedade Brasileira de Computação},
address = {Ijuí, RS, Brazil},
abstract = {Plataformas de gerenciamento IaaS como OpenStack e CloudStack, são implantadas para criação de nuvens privadas. O desempenho é importante pois impacta no tempo de disponibilização de recursos. Este artigo avalia o desempenho do gerenciamento das plataformas. Os resultados mostram uma diferença média de 66,3% na criação de instâncias. Na exclusão das instâncias, houve a diferença de 28,6%, sendo ambos resultados favoráveis ao OpenStack},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Plataformas de gerenciamento IaaS como OpenStack e CloudStack, são implantadas para criação de nuvens privadas. O desempenho é importante pois impacta no tempo de disponibilização de recursos. Este artigo avalia o desempenho do gerenciamento das plataformas. Os resultados mostram uma diferença média de 66,3% na criação de instâncias. Na exclusão das instâncias, houve a diferença de 28,6%, sendo ambos resultados favoráveis ao OpenStack |
| Filho, Renato B. H.; Griebler, Dalvan; Ledur, Cleverson; Fernandes, Luiz G. Avaliando a Produtividade e o Desempenho da DSL SPar em uma Aplicação de Detecção de Pistas Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 4, Sociedade Brasileira de Computação (SBC), Ijuí, RS, BR, 2017. @inproceedings{FILHO:ERAD:17,
title = {Avaliando a Produtividade e o Desempenho da DSL SPar em uma Aplicação de Detecção de Pistas},
author = {Renato B. H. Filho and Dalvan Griebler and Cleverson Ledur and Luiz G. Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2017/CR_ERAD_IC_Hoffmann.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {4},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {Ijuí, RS, BR},
abstract = {A linguagem de domínio específico SPar, embarcada na linguagem C++, fornece através de anotações uma alternativa para explorar o paralelismo de stream em arquiteturas multi-núcleo. Neste artigo, o objetivo é demonstrar indicadores de desempenho e produtividade em uma aplicação de detecção de pistas. Os resultados comprovaram que a SPar apresentou maior produtividade e bom desempenho.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
A linguagem de domínio específico SPar, embarcada na linguagem C++, fornece através de anotações uma alternativa para explorar o paralelismo de stream em arquiteturas multi-núcleo. Neste artigo, o objetivo é demonstrar indicadores de desempenho e produtividade em uma aplicação de detecção de pistas. Os resultados comprovaram que a SPar apresentou maior produtividade e bom desempenho. |
| Mesquita, Cassiano E.; Ledur, Cleverson; Griebler, Dalvan; Fernandes, Luiz G. Proposta de uma Plataforma para Experimentos de Software em Programação Paralela Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 4, Sociedade Brasileira de Computação (SBC), Ijuí, RS, BR, 2017. @inproceedings{MESQUITA:ERAD:17,
title = {Proposta de uma Plataforma para Experimentos de Software em Programação Paralela},
author = {Cassiano E. Mesquita and Cleverson Ledur and Dalvan Griebler and Luiz G. Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2017/CR_ERAD_PG_Mesquita_2017.pdf},
year = {2017},
date = {2017-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {4},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {Ijuí, RS, BR},
abstract = {Este artigo propõe uma plataforma web para simplificar a avaliação de interfaces de programação paralela. A ideia central é identificar as dificuldades enfrentadas por potenciais desenvolvedores a fim de propor melhorias que irão reduzir o esforço na paralelização de aplicações. A plataforma prevista é composta de uma interface web, implementada com linguagens PHP e Javascript.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Este artigo propõe uma plataforma web para simplificar a avaliação de interfaces de programação paralela. A ideia central é identificar as dificuldades enfrentadas por potenciais desenvolvedores a fim de propor melhorias que irão reduzir o esforço na paralelização de aplicações. A plataforma prevista é composta de uma interface web, implementada com linguagens PHP e Javascript. |
 | Griebler, Dalvan; Danelutto, Marco; Torquati, Massimo; Fernandes, Luiz Gustavo SPar: A DSL for High-Level and Productive Stream Parallelism Journal Article doi In: Parallel Processing Letters, vol. 27, no. 01, pp. 1740005, 2017. @article{GRIEBLER:PPL:17,
title = {SPar: A DSL for High-Level and Productive Stream Parallelism},
author = {Dalvan Griebler and Marco Danelutto and Massimo Torquati and Luiz Gustavo Fernandes},
url = {http://dx.doi.org/10.1142/S0129626417400059},
doi = {10.1142/S0129626417400059},
year = {2017},
date = {2017-03-01},
urldate = {2017-03-01},
journal = {Parallel Processing Letters},
volume = {27},
number = {01},
pages = {1740005},
publisher = {World Scientific},
abstract = {This paper introduces SPar, an internal C++ Domain-Specific Language (DSL) that supports the development of classic stream parallel applications. The DSL uses standard C++ attributes to introduce annotations tagging the notable components of stream parallel applications: stream sources and stream processing stages. A set of tools process SPar code (C++ annotated code using the SPar attributes) to generate FastFlow C++ code that exploits the stream parallelism denoted by SPar annotations while targeting shared memory multi-core architectures. We outline the main SPar features along with the main implementation techniques and tools. Also, we show the results of experiments assessing the feasibility of the entire approach as well as SPar’s performance and expressiveness.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper introduces SPar, an internal C++ Domain-Specific Language (DSL) that supports the development of classic stream parallel applications. The DSL uses standard C++ attributes to introduce annotations tagging the notable components of stream parallel applications: stream sources and stream processing stages. A set of tools process SPar code (C++ annotated code using the SPar attributes) to generate FastFlow C++ code that exploits the stream parallelism denoted by SPar annotations while targeting shared memory multi-core architectures. We outline the main SPar features along with the main implementation techniques and tools. Also, we show the results of experiments assessing the feasibility of the entire approach as well as SPar’s performance and expressiveness. |
| Vogel, Adriano; Griebler, Dalvan; Schepke, Claudio; Fernandes, Luiz Gustavo An Intra-Cloud Networking Performance Evaluation on CloudStack Environment Inproceedings doi In: 25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 5, IEEE, St. Petersburg, Russia, 2017. @inproceedings{larcc:intra-cloud_networking_cloudstack:PDP:17,
title = {An Intra-Cloud Networking Performance Evaluation on CloudStack Environment},
author = {Adriano Vogel and Dalvan Griebler and Claudio Schepke and Luiz Gustavo Fernandes},
url = {http://ieeexplore.ieee.org/document/7912689/},
doi = {10.1109/PDP.2017.40},
year = {2017},
date = {2017-03-01},
booktitle = {25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
pages = {5},
publisher = {IEEE},
address = {St. Petersburg, Russia},
series = {PDP'17},
abstract = {Infrastructure-as-a-Service (IaaS) is a cloud on-demand commodity built on top of virtualization technologies and managed by IaaS tools. In this scenario, performance is a relevant matter because a set of aspects may impact and increase the system overhead.Specific on the network, the use of virtualized capabilities may cause performance degradation (eg.,latency, throughput). The goal of this paper is to contribute to networking performance evaluation, providing new insights for private IaaS clouds. To achieve our goal, we deploy CloudStack environments and conduct experiments with different configurations and techniques. The research findings demonstrate that KVM-based cloud instances have small network performance degradation regarding throughput (about 0.2% for coarse-grained and 6.8% for fine-grained messages) while container-based instances have even better results. On the other hand, the KVM instances present worst latency (about 12.4% on coarse-grained and two times more on fine-grained messages w.r.t. native environment) and better in container-based instances, where the performance results are close to the native environment. Furthermore, we demonstrate a performance optimization of applications running on KVM.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Infrastructure-as-a-Service (IaaS) is a cloud on-demand commodity built on top of virtualization technologies and managed by IaaS tools. In this scenario, performance is a relevant matter because a set of aspects may impact and increase the system overhead.Specific on the network, the use of virtualized capabilities may cause performance degradation (eg.,latency, throughput). The goal of this paper is to contribute to networking performance evaluation, providing new insights for private IaaS clouds. To achieve our goal, we deploy CloudStack environments and conduct experiments with different configurations and techniques. The research findings demonstrate that KVM-based cloud instances have small network performance degradation regarding throughput (about 0.2% for coarse-grained and 6.8% for fine-grained messages) while container-based instances have even better results. On the other hand, the KVM instances present worst latency (about 12.4% on coarse-grained and two times more on fine-grained messages w.r.t. native environment) and better in container-based instances, where the performance results are close to the native environment. Furthermore, we demonstrate a performance optimization of applications running on KVM. |
2016
|
| Maron, Carlos A. F.; Griebler, Dalvan; Schepke, Claudio; Fernandes, Luiz Gustavo Desempenho de OpenStack e OpenNebula em Estações de Trabalho: Uma Avaliação com Microbenchmarks e NPB Journal Article doi In: Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC), vol. 1, no. 6, pp. 15, 2016. @article{larcc:nas_workstations:REABTIC:16,
title = {Desempenho de OpenStack e OpenNebula em Estações de Trabalho: Uma Avaliação com Microbenchmarks e NPB},
author = {Carlos A. F. Maron and Dalvan Griebler and Claudio Schepke and Luiz Gustavo Fernandes},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/03/MARON_REABTIC_2016.pdf},
doi = {10.5281/zenodo.345597},
year = {2016},
date = {2016-12-01},
journal = {Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC)},
volume = {1},
number = {6},
pages = {15},
publisher = {SETREM},
address = {Três de Maio, Brazil},
abstract = {IaaS (Infrastructure as a Service) clouds provide on-demand computing resources (i.e, memory, networking, storage and processing unit) for running applications. Studies that evaluate the IaaS cloud performance are limited to the virtualization layer and ignore the impact of management tools analysis. In contrast, our research investigates the impact of them in order to identify if there are influences or differences between OpenStack and OpenNebula. We used intensive workloads (microbenchmarks) and scientific parallel applications. Statistically, the results demonstrated that OpenNebula was 11.07% better using microbenchmarks and 8.41% with scientific parallel applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
IaaS (Infrastructure as a Service) clouds provide on-demand computing resources (i.e, memory, networking, storage and processing unit) for running applications. Studies that evaluate the IaaS cloud performance are limited to the virtualization layer and ignore the impact of management tools analysis. In contrast, our research investigates the impact of them in order to identify if there are influences or differences between OpenStack and OpenNebula. We used intensive workloads (microbenchmarks) and scientific parallel applications. Statistically, the results demonstrated that OpenNebula was 11.07% better using microbenchmarks and 8.41% with scientific parallel applications. |
| Maron, Carlos A. F.; Vogel, Adriano; Benedetti, Vera L. L.; Shubeita, Fauzi; Schepke, Claudio; Griebler, Dalvan Panorama Geral e Resultados do Projeto HiPerfCloud Inproceedings In: 15th Jornada de Pesquisa SETREM, pp. 4, SETREM, Três de Maio, Brazil, 2016. @inproceedings{larcc:hiperfcloud:JP:16,
title = {Panorama Geral e Resultados do Projeto HiPerfCloud},
author = {Carlos A. F. Maron and Adriano Vogel and Vera L. L. Benedetti and Fauzi Shubeita and Claudio Schepke and Dalvan Griebler},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/03/HiPerfCloud_JP_SETREM_2016.pdf},
year = {2016},
date = {2016-10-01},
booktitle = {15th Jornada de Pesquisa SETREM},
pages = {4},
publisher = {SETREM},
address = {Três de Maio, Brazil},
abstract = {O projeto HiPerfCloud, em andamento no LARCC da Faculdade SETREM, desenvolve pesquisas em nível de infraestrutura em nuvens computacionais. O objetivo do projeto é analisar o impacto que aplicações científicas de alto desempenho sofrem quando executadas em nuvens privadas e avaliar as tecnologias de implantação envolvidas. As publicações de artigos em eventos nacionais e internacionais do projeto tem colaborado com o estado da arte da área. As descobertas recentes apontaram que aspectos de infraestrutura, rede e virtualização, exercem influência no desempenho de aplicações executadas em nuvem, enquanto as ferramentas de IaaS possuem contrastes em relação ao gerenciamento (escalonamento, disponibilidade, segurança).},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
O projeto HiPerfCloud, em andamento no LARCC da Faculdade SETREM, desenvolve pesquisas em nível de infraestrutura em nuvens computacionais. O objetivo do projeto é analisar o impacto que aplicações científicas de alto desempenho sofrem quando executadas em nuvens privadas e avaliar as tecnologias de implantação envolvidas. As publicações de artigos em eventos nacionais e internacionais do projeto tem colaborado com o estado da arte da área. As descobertas recentes apontaram que aspectos de infraestrutura, rede e virtualização, exercem influência no desempenho de aplicações executadas em nuvem, enquanto as ferramentas de IaaS possuem contrastes em relação ao gerenciamento (escalonamento, disponibilidade, segurança). |
| Pieper, Ricardo; Griebler, Dalvan; Lovato, Adalberto Towards a Software as a Service for Biodigestor Analytics Journal Article doi In: Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC), vol. 1, no. 5, pp. 15, 2016. @article{larcc:saas_analytics:REABTIC:16,
title = {Towards a Software as a Service for Biodigestor Analytics},
author = {Ricardo Pieper and Dalvan Griebler and Adalberto Lovato},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/04/PIEPER_REABTIC_2016.pdf},
doi = {10.5281/zenodo.345587},
year = {2016},
date = {2016-08-01},
journal = {Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC)},
volume = {1},
number = {5},
pages = {15},
publisher = {SETREM},
address = {Três de Maio, Brazil},
abstract = {The field of machine learning is becoming even more important in the last years. The ever-increasing amount of data and complexity of computational problems challenges the currently available technology. Meanwhile, anaerobic digesters represent a good alternative for renewable energy production in Brazil. However, performing efficient and accurate predictions/analytics while completely abstracting machine learning details from end-users might not be a simple task to achieve. Usually, such tools are made for a specific scenario and may not fit with particular and general needs. Our goal was to create a SaaS for biogas data analytics by using a neural network. Therefore, an open source, cloud-enabled SaaS (Software as a Service) was developed and deployed in LARCC (Laboratory of Advanced Researches on Cloud Computing) at SETREM. The results have shown the SaaS application is able to perform predictions. The neural network's accuracy is not significantly worse than a state-of-the-art implementation, and its training speed is faster. The user interface demonstrates to be intuitive, and the predictions were accurate when providing the training algorithm with sufficient data. In addition, the file processing and network training time were good enough under traditional workload conditions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The field of machine learning is becoming even more important in the last years. The ever-increasing amount of data and complexity of computational problems challenges the currently available technology. Meanwhile, anaerobic digesters represent a good alternative for renewable energy production in Brazil. However, performing efficient and accurate predictions/analytics while completely abstracting machine learning details from end-users might not be a simple task to achieve. Usually, such tools are made for a specific scenario and may not fit with particular and general needs. Our goal was to create a SaaS for biogas data analytics by using a neural network. Therefore, an open source, cloud-enabled SaaS (Software as a Service) was developed and deployed in LARCC (Laboratory of Advanced Researches on Cloud Computing) at SETREM. The results have shown the SaaS application is able to perform predictions. The neural network's accuracy is not significantly worse than a state-of-the-art implementation, and its training speed is faster. The user interface demonstrates to be intuitive, and the predictions were accurate when providing the training algorithm with sufficient data. In addition, the file processing and network training time were good enough under traditional workload conditions. |
| Barth, Andréia; Wolfer, Camila; Lovato, Adalberto; Griebler, Dalvan Avaliação da Irradiação Solar como Fonte de Energia Renovável no Noroeste do Estado do Rio Grande do Sul Através de Uma Rede Neural Journal Article doi In: Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC), vol. 1, no. 5, pp. 15, 2016. @article{larcc:neural_networks:REABTIC:16,
title = {Avaliação da Irradiação Solar como Fonte de Energia Renovável no Noroeste do Estado do Rio Grande do Sul Através de Uma Rede Neural},
author = {Andréia Barth and Camila Wolfer and Adalberto Lovato and Dalvan Griebler},
url = {http://larcc.setrem.com.br/wp-content/uploads/2018/02/ANDREIA_CAMILA_REABTIC_2016.pdf},
doi = {10.5281/zenodo.345585},
year = {2016},
date = {2016-08-01},
journal = {Revista Eletrônica Argentina-Brasil de Tecnologias da Informação e da Comunicação (REABTIC)},
volume = {1},
number = {5},
pages = {15},
publisher = {SETREM},
address = {Três de Maio, RS, Brazil},
abstract = {Solar irradiation is one of the cleanest renewable energy sources of nowadays. In this work, the goal was to implement a neural network capable of evaluating the solar irradiation in the Northwest region of Rio Grande do Sul. In case, this assessment targets meteorological data, from January to April 2015. The network Perceptron was implemented and trained using MATLAB software. The results have indicated that the system obtained a highly accurate and that the region is a good enough place for stemmed energy production of solar irradiation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Solar irradiation is one of the cleanest renewable energy sources of nowadays. In this work, the goal was to implement a neural network capable of evaluating the solar irradiation in the Northwest region of Rio Grande do Sul. In case, this assessment targets meteorological data, from January to April 2015. The network Perceptron was implemented and trained using MATLAB software. The results have indicated that the system obtained a highly accurate and that the region is a good enough place for stemmed energy production of solar irradiation. |
| Griebler, Dalvan Domain-Specific Language & Support Tool for High-Level Stream Parallelism PhD Thesis Faculdade de Informática - PPGCC - PUCRS, 2016. @phdthesis{GRIEBLER:PHD:16,
title = {Domain-Specific Language & Support Tool for High-Level Stream Parallelism},
author = {Dalvan Griebler},
url = {http://tede2.pucrs.br/tede2/handle/tede/6776},
year = {2016},
date = {2016-06-01},
address = {Porto Alegre, Brazil},
school = {Faculdade de Informática - PPGCC - PUCRS},
abstract = {Stream-based systems are representative of several application domains including video, audio, networking, graphic processing, etc. Stream programs may run on different kinds of parallel architectures (desktop, servers, cell phones, and supercomputers) and represent significant workloads on our current computing systems. Nevertheless, most of them are still not parallelized. Moreover, when new software has to be developed, programmers often face a trade-off between coding productivity, code portability, and performance. To solve this problem, we provide a new Domain-Specific Language (DSL) that naturally/on-the-fly captures and represents parallelism for stream-based applications. The aim is to offer a set of attributes (through annotations) that preserves the program's source code and is not architecture-dependent for annotating parallelism. We used the C++ attribute mechanism to design a ``textitde-facto'' standard C++ embedded DSL named SPar. However, the implementation of DSLs using compiler-based tools is difficult, complicated, and usually requires a significant learning curve. This is even harder for those who are not familiar with compiler technology. Therefore, our motivation is to simplify this path for other researchers (experts in their domain) with support tools (our tool is CINCLE) to create high-level and productive DSLs through powerful and aggressive source-to-source transformations. In fact, parallel programmers can use their expertise without having to design and implement low-level code. The main goal of this thesis was to create a DSL and support tools for high-level stream parallelism in the context of a programming framework that is compiler-based and domain-oriented. Thus, we implemented SPar using CINCLE. SPar supports the software developer with productivity, performance, and code portability while CINCLE provides sufficient support to generate new DSLs. Also, SPar targets source-to-source transformation producing parallel pattern code built on top of FastFlow and MPI. Finally, we provide a full set of experiments showing that SPar provides better coding productivity without significant performance degradation in multi-core systems as well as transformation rules that are able to achieve code portability (for cluster architectures) through its generalized attributes.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
Stream-based systems are representative of several application domains including video, audio, networking, graphic processing, etc. Stream programs may run on different kinds of parallel architectures (desktop, servers, cell phones, and supercomputers) and represent significant workloads on our current computing systems. Nevertheless, most of them are still not parallelized. Moreover, when new software has to be developed, programmers often face a trade-off between coding productivity, code portability, and performance. To solve this problem, we provide a new Domain-Specific Language (DSL) that naturally/on-the-fly captures and represents parallelism for stream-based applications. The aim is to offer a set of attributes (through annotations) that preserves the program's source code and is not architecture-dependent for annotating parallelism. We used the C++ attribute mechanism to design a ``textitde-facto'' standard C++ embedded DSL named SPar. However, the implementation of DSLs using compiler-based tools is difficult, complicated, and usually requires a significant learning curve. This is even harder for those who are not familiar with compiler technology. Therefore, our motivation is to simplify this path for other researchers (experts in their domain) with support tools (our tool is CINCLE) to create high-level and productive DSLs through powerful and aggressive source-to-source transformations. In fact, parallel programmers can use their expertise without having to design and implement low-level code. The main goal of this thesis was to create a DSL and support tools for high-level stream parallelism in the context of a programming framework that is compiler-based and domain-oriented. Thus, we implemented SPar using CINCLE. SPar supports the software developer with productivity, performance, and code portability while CINCLE provides sufficient support to generate new DSLs. Also, SPar targets source-to-source transformation producing parallel pattern code built on top of FastFlow and MPI. Finally, we provide a full set of experiments showing that SPar provides better coding productivity without significant performance degradation in multi-core systems as well as transformation rules that are able to achieve code portability (for cluster architectures) through its generalized attributes. |
| Griebler, Dalvan Domain-Specific Language & Support Tool for High-Level Stream Parallelism PhD Thesis Computer Science Department - University of Pisa, 2016. @phdthesis{GRIEBLER:PHD_PISA:16,
title = {Domain-Specific Language & Support Tool for High-Level Stream Parallelism},
author = {Dalvan Griebler},
url = {https://gmap.pucrs.br/dalvan/papers/2016/thesis_dalvan_UNIPI_2016.pdf},
year = {2016},
date = {2016-04-01},
address = {Pisa, Italy},
school = {Computer Science Department - University of Pisa},
abstract = {Stream-based systems are representative of several application domains including video, audio, networking, graphic processing, etc. Stream programs may run on different kinds of parallel architectures (desktop, servers, cell phones, and supercomputers) and represent significant workloads on our current computing systems. Nevertheless, most of them are still not parallelized. Moreover, when new software has to be developed, programmers often face a trade-off between coding productivity, code portability, and performance. To solve this problem, we provide a new Domain-Specific Language (DSL) that naturally/on-the-fly captures and represents parallelism for stream-based applications. The aim is to offer a set of attributes (through annotations) that preserves the program's source code and is not architecture-dependent for annotating parallelism. We used the C++ attribute mechanism to design a ``textitde-facto'' standard C++ embedded DSL named SPar. However, the implementation of DSLs using compiler-based tools is difficult, complicated, and usually requires a significant learning curve. This is even harder for those who are not familiar with compiler technology. Therefore, our motivation is to simplify this path for other researchers (experts in their domain) with support tools (our tool is CINCLE) to create high-level and productive DSLs through powerful and aggressive source-to-source transformations. In fact, parallel programmers can use their expertise without having to design and implement low-level code. The main goal of this thesis was to create a DSL and support tools for high-level stream parallelism in the context of a programming framework that is compiler-based and domain-oriented. Thus, we implemented SPar using CINCLE. SPar supports the software developer with productivity, performance, and code portability while CINCLE provides sufficient support to generate new DSLs. Also, SPar targets source-to-source transformation producing parallel pattern code built on top of FastFlow and MPI. Finally, we provide a full set of experiments showing that SPar provides better coding productivity without significant performance degradation in multi-core systems as well as transformation rules that are able to achieve code portability (for cluster architectures) through its generalized attributes.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
Stream-based systems are representative of several application domains including video, audio, networking, graphic processing, etc. Stream programs may run on different kinds of parallel architectures (desktop, servers, cell phones, and supercomputers) and represent significant workloads on our current computing systems. Nevertheless, most of them are still not parallelized. Moreover, when new software has to be developed, programmers often face a trade-off between coding productivity, code portability, and performance. To solve this problem, we provide a new Domain-Specific Language (DSL) that naturally/on-the-fly captures and represents parallelism for stream-based applications. The aim is to offer a set of attributes (through annotations) that preserves the program's source code and is not architecture-dependent for annotating parallelism. We used the C++ attribute mechanism to design a ``textitde-facto'' standard C++ embedded DSL named SPar. However, the implementation of DSLs using compiler-based tools is difficult, complicated, and usually requires a significant learning curve. This is even harder for those who are not familiar with compiler technology. Therefore, our motivation is to simplify this path for other researchers (experts in their domain) with support tools (our tool is CINCLE) to create high-level and productive DSLs through powerful and aggressive source-to-source transformations. In fact, parallel programmers can use their expertise without having to design and implement low-level code. The main goal of this thesis was to create a DSL and support tools for high-level stream parallelism in the context of a programming framework that is compiler-based and domain-oriented. Thus, we implemented SPar using CINCLE. SPar supports the software developer with productivity, performance, and code portability while CINCLE provides sufficient support to generate new DSLs. Also, SPar targets source-to-source transformation producing parallel pattern code built on top of FastFlow and MPI. Finally, we provide a full set of experiments showing that SPar provides better coding productivity without significant performance degradation in multi-core systems as well as transformation rules that are able to achieve code portability (for cluster architectures) through its generalized attributes. |
| Bairros, Gildomiro; Griebler, Dalvan; Fernandes, Luiz Gustavo Proposta de Suporte a Elasticidade Automática em Nuvem para uma Linguagem Específica de Domínio Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 197-198, Sociedade Brasileira de Computação (SBC), São Leopoldo, RS, BR, 2016. @inproceedings{BAIRROS:ERAD:16,
title = {Proposta de Suporte a Elasticidade Automática em Nuvem para uma Linguagem Específica de Domínio},
author = {Gildomiro Bairros and Dalvan Griebler and Luiz Gustavo Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2016/CR_ERAD_PG__2016.pdf},
year = {2016},
date = {2016-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {197-198},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {São Leopoldo, RS, BR},
abstract = {Este artigo apresenta uma proposta de desenvolvimento de um middleware para prover elasticidade para aplicações desenvolvidas com uma linguagem específica de domínio voltada para o paralelismo de stream. O middleware atuará a nível de PaaS e colocará instruções de elasticidade de forma transparente ao desenvolvedor, fazendo o parser do código e injetando automaticamente as instruções de elasticidade.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Este artigo apresenta uma proposta de desenvolvimento de um middleware para prover elasticidade para aplicações desenvolvidas com uma linguagem específica de domínio voltada para o paralelismo de stream. O middleware atuará a nível de PaaS e colocará instruções de elasticidade de forma transparente ao desenvolvedor, fazendo o parser do código e injetando automaticamente as instruções de elasticidade. |
| Vogel, Adriano; Maron, Carlos A. F.; Griebler, Dalvan; Schepke, Claudio Medindo o Desempenho de Implantações de OpenStack, CloudStack e OpenNebula em Aplicações Científicas Inproceedings In: 16th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS), pp. 279-282, Sociedade Brasileira de Computação, São Leopoldo, RS, Brazil, 2016. @inproceedings{hiperfcloud:nas_all:ERAD:16,
title = {Medindo o Desempenho de Implantações de OpenStack, CloudStack e OpenNebula em Aplicações Científicas},
author = {Adriano Vogel and Carlos A. F. Maron and Dalvan Griebler and Claudio Schepke},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/03/VOGEL_ERAD_2016.pdf},
year = {2016},
date = {2016-04-01},
booktitle = {16th Escola Regional de Alto Desempenho do Estado do Rio Grande do Sul (ERAD/RS)},
pages = {279-282},
publisher = {Sociedade Brasileira de Computação},
address = {São Leopoldo, RS, Brazil},
abstract = {Ambientes de nuvem possibilitam a execução de aplicações sob demanda e são uma alternativa para aplicações científicas. O desempenho é um dos principais desafios, devido ao uso da virtualização que induz perdas e variações. O objetivo do trabalho foi implantar ambientes de nuvem privada com diferentes ferramentas de IaaS, medindo o desempenho de aplicações paralelas. Consequentemente, os resultados apresentaram poucos contrastes.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Ambientes de nuvem possibilitam a execução de aplicações sob demanda e são uma alternativa para aplicações científicas. O desempenho é um dos principais desafios, devido ao uso da virtualização que induz perdas e variações. O objetivo do trabalho foi implantar ambientes de nuvem privada com diferentes ferramentas de IaaS, medindo o desempenho de aplicações paralelas. Consequentemente, os resultados apresentaram poucos contrastes. |
| Maron, Carlos A. F.; Griebler, Dalvan; Fernandes, Luiz Gustavo Em Direção à um Benchmark de Workload Sintético para Paralelismo de Stream em Arquiteturas Multicore Inproceedings In: Escola Regional de Alto Desempenho (ERAD-RS), pp. 171-172, Sociedade Brasileira de Computação (SBC), São Leopoldo, RS, BR, 2016. @inproceedings{MARON:ERAD:16,
title = {Em Direção à um Benchmark de Workload Sintético para Paralelismo de Stream em Arquiteturas Multicore},
author = {Carlos A. F. Maron and Dalvan Griebler and Luiz Gustavo Fernandes},
url = {https://gmap.pucrs.br/dalvan/papers/2016/CR_ERAD_PG_2016.pdf},
year = {2016},
date = {2016-04-01},
booktitle = {Escola Regional de Alto Desempenho (ERAD-RS)},
pages = {171-172},
publisher = {Sociedade Brasileira de Computação (SBC)},
address = {São Leopoldo, RS, BR},
abstract = {O processamento de fluxos contínuos de dados (stream) está provocando novos desafios na exploração de paralelismo. Suítes clássicas de benchmarks não exploram totalmente os aspectos de stream, focando-se em problemas de natureza científica e execução finita. Para endereçar este problema em ambientes de memória compartilhada, o trabalho propõe um benchmark de workload sintético voltado para paralelismo stream},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
O processamento de fluxos contínuos de dados (stream) está provocando novos desafios na exploração de paralelismo. Suítes clássicas de benchmarks não exploram totalmente os aspectos de stream, focando-se em problemas de natureza científica e execução finita. Para endereçar este problema em ambientes de memória compartilhada, o trabalho propõe um benchmark de workload sintético voltado para paralelismo stream |
| Vogel, Adriano; Griebler, Dalvan; Maron, Carlos A. F.; Schepke, Claudio; Fernandes, Luiz Gustavo Private IaaS Clouds: A Comparative Analysis of OpenNebula, CloudStack and OpenStack Inproceedings doi In: 24th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 672-679, IEEE, Heraklion Crete, Greece, 2016. @inproceedings{larcc:IaaS_private:PDP:16,
title = {Private IaaS Clouds: A Comparative Analysis of OpenNebula, CloudStack and OpenStack},
author = {Adriano Vogel and Dalvan Griebler and Carlos A. F. Maron and Claudio Schepke and Luiz Gustavo Fernandes},
url = {http://ieeexplore.ieee.org/document/7445407/},
doi = {10.1109/PDP.2016.75},
year = {2016},
date = {2016-02-01},
booktitle = {24th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
pages = {672-679},
publisher = {IEEE},
address = {Heraklion Crete, Greece},
series = {PDP'16},
abstract = {Despite the evolution of cloud computing in recent years, the performance and comprehensive understanding of the available private cloud tools are still under research. This paper contributes to an analysis of the Infrastructure as a Service (IaaS) domain by mapping new insights and discussing the challenges for improving cloud services. The goal is to make a comparative analysis of OpenNebula, OpenStack and CloudStack tools, evaluating their differences on support for flexibility and resiliency. Also, we aim at evaluating these three cloud tools when they are deployed using a mutual hypervisor (KVM) for discovering new empirical insights. Our research results demonstrated that OpenStack is the most resilient and CloudStack is the most flexible for deploying an IaaS private cloud. Moreover, the performance experiments indicated some contrasts among the private IaaS cloud instances when running intensive workloads and scientific applications.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Despite the evolution of cloud computing in recent years, the performance and comprehensive understanding of the available private cloud tools are still under research. This paper contributes to an analysis of the Infrastructure as a Service (IaaS) domain by mapping new insights and discussing the challenges for improving cloud services. The goal is to make a comparative analysis of OpenNebula, OpenStack and CloudStack tools, evaluating their differences on support for flexibility and resiliency. Also, we aim at evaluating these three cloud tools when they are deployed using a mutual hypervisor (KVM) for discovering new empirical insights. Our research results demonstrated that OpenStack is the most resilient and CloudStack is the most flexible for deploying an IaaS private cloud. Moreover, the performance experiments indicated some contrasts among the private IaaS cloud instances when running intensive workloads and scientific applications. |
2015
|
 | Adornes, Daniel; Griebler, Dalvan; Ledur, Cleverson; Fernandes, Luiz G. Coding Productivity in MapReduce Applications for Distributed and Shared Memory Architectures Journal Article doi In: International Journal of Software Engineering and Knowledge Engineering, vol. 25, no. 10, pp. 1739-1741, 2015. @article{ADORNES:IJSEKE:15,
title = {Coding Productivity in MapReduce Applications for Distributed and Shared Memory Architectures},
author = {Daniel Adornes and Dalvan Griebler and Cleverson Ledur and Luiz G. Fernandes},
url = {http://dx.doi.org/10.1142/S0218194015710096},
doi = {10.1142/S0218194015710096},
year = {2015},
date = {2015-12-01},
urldate = {2015-12-01},
journal = {International Journal of Software Engineering and Knowledge Engineering},
volume = {25},
number = {10},
pages = {1739-1741},
publisher = {World Scientific},
abstract = {MapReduce was originally proposed as a suitable and efficient approach for analyzing and processing large amounts of data. Since then, many researches contributed with MapReduce implementations for distributed and shared memory architectures. Nevertheless, different architectural levels require different optimization strategies in order to achieve high-performance computing. Such strategies in turn have caused very different MapReduce programming interfaces among these researches. This paper presents some research notes on coding productivity when developing MapReduce applications for distributed and shared memory architectures. As a case study, we introduce our current research on a unified MapReduce domain-specific language with code generation for Hadoop and Phoenix++, which has achieved a coding productivity increase from 41.84% and up to 94.71% without significant performance losses (below 3%) compared to those frameworks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
MapReduce was originally proposed as a suitable and efficient approach for analyzing and processing large amounts of data. Since then, many researches contributed with MapReduce implementations for distributed and shared memory architectures. Nevertheless, different architectural levels require different optimization strategies in order to achieve high-performance computing. Such strategies in turn have caused very different MapReduce programming interfaces among these researches. This paper presents some research notes on coding productivity when developing MapReduce applications for distributed and shared memory architectures. As a case study, we introduce our current research on a unified MapReduce domain-specific language with code generation for Hadoop and Phoenix++, which has achieved a coding productivity increase from 41.84% and up to 94.71% without significant performance losses (below 3%) compared to those frameworks. |
| Ledur, Cleverson; Griebler, Dalvan; Manssour, Isabel; Fernandes, Luiz G. Towards a Domain-Specific Language for Geospatial Data Visualization Maps with Big Data Sets Inproceedings doi In: ACS/IEEE International Conference on Computer Systems and Applications, pp. 8, IEEE, Marrakech, Marrocos, 2015. @inproceedings{LEDUR:AICCSA:15,
title = {Towards a Domain-Specific Language for Geospatial Data Visualization Maps with Big Data Sets},
author = {Cleverson Ledur and Dalvan Griebler and Isabel Manssour and Luiz G. Fernandes},
url = {http://dx.doi.org/10.1109/AICCSA.2015.7507178},
doi = {10.1109/AICCSA.2015.7507178},
year = {2015},
date = {2015-11-01},
booktitle = {ACS/IEEE International Conference on Computer Systems and Applications},
pages = {8},
publisher = {IEEE},
address = {Marrakech, Marrocos},
series = {AICCSA'15},
abstract = {Data visualization is an alternative for representing information and helping people gain faster insights. However, the programming/creating of a visualization for large data sets is still a challenging task for users with low-level of software development knowledge. Our goal is to increase the productivity of experts who are familiar with the application domain. Therefore, we proposed an external Domain-Specific Language (DSL) that allows massive input of raw data and provides a small dictionary with suitable data visualization keywords. Also, we implemented it to support efficient data filtering operations and generate HTML or Javascript output code files (using Google Maps API). To measure the potential of our DSL, we evaluated four types of geospatial data visualization maps with four different technologies. The experiment results demonstrated a productivity gain when compared to the traditional way of implementing (e.g., Google Maps API, OpenLayers, and Leaflet), and efficient algorithm implementation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Data visualization is an alternative for representing information and helping people gain faster insights. However, the programming/creating of a visualization for large data sets is still a challenging task for users with low-level of software development knowledge. Our goal is to increase the productivity of experts who are familiar with the application domain. Therefore, we proposed an external Domain-Specific Language (DSL) that allows massive input of raw data and provides a small dictionary with suitable data visualization keywords. Also, we implemented it to support efficient data filtering operations and generate HTML or Javascript output code files (using Google Maps API). To measure the potential of our DSL, we evaluated four types of geospatial data visualization maps with four different technologies. The experiment results demonstrated a productivity gain when compared to the traditional way of implementing (e.g., Google Maps API, OpenLayers, and Leaflet), and efficient algorithm implementation. |
| Vogel, Adriano; Maron, Carlos A. F.; Benedetti, Vera L. L.; Shubeita, Fauzi; Schepke, Claudio; Griebler, Dalvan HiPerfCloud: Um Projeto de Alto Desempenho em Nuvem Inproceedings In: 14th Jornada de Pesquisa SETREM, pp. 4, SETREM, Três de Maio, Brazil, 2015. @inproceedings{larcc:hiperfcloud:JP:15,
title = {HiPerfCloud: Um Projeto de Alto Desempenho em Nuvem},
author = {Adriano Vogel and Carlos A. F. Maron and Vera L. L. Benedetti and Fauzi Shubeita and Claudio Schepke and Dalvan Griebler},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/03/HiPerfCloud_JP_SETREM_2015.pdf},
year = {2015},
date = {2015-10-01},
booktitle = {14th Jornada de Pesquisa SETREM},
pages = {4},
publisher = {SETREM},
address = {Três de Maio, Brazil},
abstract = {Computação em nuvem é uma necessidade real para os ambientes de pesquisas e empresas. Embora bastante usada e estudada, ela ainda traz diversos desafios. Um deles é a obtenção de alto desempenho, sendo o principal foco do projeto HiPerfCloud. Esta é uma tarefa complexa, pois é preciso combinar tecnologias, avaliar modelos de implantação e usar soluções adequadas. Este artigo irá apresentar o projeto de pesquisa, seus principais objetivos e os principais resultados alcançados até o momento. Além disso, demonstrar as perspectivas da pesquisa no projeto.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Computação em nuvem é uma necessidade real para os ambientes de pesquisas e empresas. Embora bastante usada e estudada, ela ainda traz diversos desafios. Um deles é a obtenção de alto desempenho, sendo o principal foco do projeto HiPerfCloud. Esta é uma tarefa complexa, pois é preciso combinar tecnologias, avaliar modelos de implantação e usar soluções adequadas. Este artigo irá apresentar o projeto de pesquisa, seus principais objetivos e os principais resultados alcançados até o momento. Além disso, demonstrar as perspectivas da pesquisa no projeto. |
| Griebler, Dalvan; Danelutto, Marco; Torquati, Massimo; Fernandes, Luiz G. An Embedded C++ Domain-Specific Language for Stream Parallelism Inproceedings doi In: Parallel Computing: On the Road to Exascale, Proceedings of the International Conference on Parallel Computing, pp. 317-326, IOS Press, Edinburgh, Scotland, UK, 2015. @inproceedings{GRIEBLER:PARCO:15,
title = {An Embedded C++ Domain-Specific Language for Stream Parallelism},
author = {Dalvan Griebler and Marco Danelutto and Massimo Torquati and Luiz G. Fernandes},
url = {http://dx.doi.org/10.3233/978-1-61499-621-7-317},
doi = {10.3233/978-1-61499-621-7-317},
year = {2015},
date = {2015-09-01},
booktitle = {Parallel Computing: On the Road to Exascale, Proceedings of the International Conference on Parallel Computing},
pages = {317-326},
publisher = {IOS Press},
address = {Edinburgh, Scotland, UK},
series = {ParCo'15},
abstract = {This paper proposes a new C++ embedded Domain-Specific Language (DSL) for expressing stream parallelism by using standard C++11 attributes annotations. The main goal is to introduce high-level parallel abstractions for developing stream based parallel programs as well as reducing sequential source code rewriting. We demonstrated that by using a small set of attributes it is possible to produce different parallel versions depending on the way the source code is annotated. The performances of the parallel code produced are comparable with those obtained by manual parallelization.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper proposes a new C++ embedded Domain-Specific Language (DSL) for expressing stream parallelism by using standard C++11 attributes annotations. The main goal is to introduce high-level parallel abstractions for developing stream based parallel programs as well as reducing sequential source code rewriting. We demonstrated that by using a small set of attributes it is possible to produce different parallel versions depending on the way the source code is annotated. The performances of the parallel code produced are comparable with those obtained by manual parallelization. |
| Roveda, Demétrius; Vogel, Adriano; Maron, Carlos A. F.; Griebler, Dalvan; Schepke, Claudio Analisando a Camada de Gerenciamento das Ferramentas CloudStack e OpenStack para Nuvens Privadas Inproceedings In: 13th Escola Regional de Redes de Computadores (ERRC), pp. 8, Sociedade Brasileira de Computação, Passo Fundo, Brazil, 2015. @inproceedings{larcc:cloudstack_openstack:ERRC:15,
title = {Analisando a Camada de Gerenciamento das Ferramentas CloudStack e OpenStack para Nuvens Privadas},
author = {Demétrius Roveda and Adriano Vogel and Carlos A. F. Maron and Dalvan Griebler and Claudio Schepke},
url = {http://larcc.setrem.com.br/wp-content/uploads/2017/04/ROVEDA_ERRC_2015.pdf},
year = {2015},
date = {2015-09-01},
booktitle = {13th Escola Regional de Redes de Computadores (ERRC)},
pages = {8},
publisher = {Sociedade Brasileira de Computação},
address = {Passo Fundo, Brazil},
abstract = {A camada de gerenciamento é um dos elementos mais importantes para o modelo de serviço IaaS nas ferramentas de administração de nuvem privada. Isso porque oferece aos usuários/clientes os recursos de infraestrutura sob-demanda e controla questões administrativas da nuvem. Nesse artigo, o objetivo é realizar uma análise da interface de gerenciamento das ferramentas CloudStack e OpenStack. Com o estudo realizado, constatou-se que as ferramentas tem gerenciamento distinto. No entanto, OpenStack se mostrou mais robusto e complexo, enquanto CloudStack é mais centralizado e possui uma interface gráfica mais completa e intuitiva.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
A camada de gerenciamento é um dos elementos mais importantes para o modelo de serviço IaaS nas ferramentas de administração de nuvem privada. Isso porque oferece aos usuários/clientes os recursos de infraestrutura sob-demanda e controla questões administrativas da nuvem. Nesse artigo, o objetivo é realizar uma análise da interface de gerenciamento das ferramentas CloudStack e OpenStack. Com o estudo realizado, constatou-se que as ferramentas tem gerenciamento distinto. No entanto, OpenStack se mostrou mais robusto e complexo, enquanto CloudStack é mais centralizado e possui uma interface gráfica mais completa e intuitiva. |
