Impact of parallel programming models and CPUs clock frequency on energy consumption of HPC systems

Balladini, Javier; Suppi, Remo; Rexachs, Dolores; Luque, Emilio

doi:10.1109/aiccsa.2011.6126618

Cited by 15 publications

(7 citation statements)

References 5 publications

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“…b) Comparação de Interfaces de Programação Paralela. [Balladini et al 2011] analisam a influência da exploração do paralelismo com OpenMP e MPI no consumo de energia de aplicações paralelas. [Porterfield et al 2013] apresentam uma análise dos fatores que afetam o desempenho e consumo de energia de aplicações implementadas com OpenMP. ]…”

Section: Trabalhos Relacionadosunclassified

Otimizando a correspondência de patches para o inpainting de imagens com diferentes interfaces de programação paralela

Pereira¹,

Castro²,

Serpa³

et al. 2020

Anais Do XXI Simpósio Em Sistemas Computacionais De Alto Desempenho (SSCAD 2020)

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Diversos problemas da área de processamento de imagens demandam um alto esforço computacional, como, por exemplo, os métodos de inpainting baseados na replicação de patches. Estes métodos viabilizam a solução de problemas reais, como a reconstrução de regiões sem conteúdo em imagens. Portanto, eles podem se beneﬁciar da exploração do paralelismo no nível de threads (TLP) através de interfaces de programação paralela (IPPs). No entanto, como cada IPP possui diferentes características com respeito ao gerenciamento de threads, escolher a ideal para implementar uma aplicação é importante para obter o melhor custo-benefício entre desempenho e consumo de energia, representado pelo energy-delay product (EDP). Considerando o exposto, neste trabalho, nós analisamos o potencial de exploração de paralelismo de um algoritmo de inpainting amplamente difundido na literatura com diferentes IPPs (PThreads, OpenMP, OmpSs-2 e OpenACC) e mostramos qual IPP proporciona o melhor desempenho, consumo de energia e EDP para três arquiteturas multicore e duas GPUs. Através de um conjunto de experimentos, os resultados mostram que OpenMP explorando TLP com laços paralelos é melhor para processadores AMD, enquanto que o OmpSs-2 apresenta melhores resultados nos processadores Intel.

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Section: Trabalhos Relacionadosunclassified

Otimizando a correspondência de patches para o inpainting de imagens com diferentes interfaces de programação paralela

Pereira¹,

Castro²,

Serpa³

et al. 2020

Anais Do XXI Simpósio Em Sistemas Computacionais De Alto Desempenho (SSCAD 2020)

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“…The authors in [12] have compared High Performance Computing (HPC) systems using different CPU clock frequencies. They demonstrate that the model of parallel programming (i.e., shared memory or message passing) has a major impact on the execution time and energy consumption of the applications.…”

Section: Related Workmentioning

confidence: 99%

On the influence of static power consumption in multicore embedded systems

Lorenzon

Márcia

Beck

2015

2015 IEEE International Symposium on Circuits and Systems (ISCAS)

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Energy consumption in multicore embedded systems has become a constant concern. Thread-Level Parallelism exploitation may reduce energy consumption because it saves static power consumption of the processor, since performance is obtained. However, as will be shown in this paper, the influence of the static power on the energy consumption and Energy-Delay Product will depend on how significant it is in the processor. By evaluating different levels of static power in the respect to the total power consumption in two embedded processors (ARM and Atom), we demonstrate that if the right value of static power consumption is tuned during the designing and manufacturing, it is possible to save up 35% in energy consumption and achieve up to 20% of improvements in the EDP efficiency (i.e., the best possible use of the available resources). We also show that the more communication the parallel application has, the lower is the impact of static power of the processor in the total energy consumption.

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“…The authors in [11] compared OpenMP with MPI on High Performance Computing (HPC) systems using different CPU clock frequencies. They demonstrate that the PPI has a major impact on the execution time and energy consumption of the applications.…”

Section: Related Workmentioning

confidence: 99%

The Influence of Parallel Programming Interfaces on Multicore Embedded Systems

Lorenzon

Sartor

Márcia

et al. 2015

2015 IEEE 39th Annual Computer Software and Applications Conference

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Thread-Level Parallelism (TLP) exploitation for embedded systems has been a challenge for software developers: while it is necessary to take advantage of the availability of multiple cores, it is also mandatory to consume less energy. To speed up the development process and make it as transparent as possible, software designers use Parallel Programming Interfaces (PPIs). However, as will be shown in this paper, each PPI implements different ways to exchange data using shared memory regions, influencing performance, energy consumption and Energy-Delay Product (EDP), which varies across different embedded processors. By evaluating four PPIs and three multicore processors (ARM A8, A9 and Intel Atom), we demonstrate that by simply switching PPI it is possible to save up to 59% in energy consumption and achieve up to 85% of EDP improvements, in the most significant case. We also show that the efficiency (i.e., the best possible use of the available resources) decreases as the number of threads increases in almost all cases, but at distinct rates.

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Impact of parallel programming models and CPUs clock frequency on energy consumption of HPC systems

Cited by 15 publications

References 5 publications

Otimizando a correspondência de patches para o inpainting de imagens com diferentes interfaces de programação paralela

Otimizando a correspondência de patches para o inpainting de imagens com diferentes interfaces de programação paralela

On the influence of static power consumption in multicore embedded systems

The Influence of Parallel Programming Interfaces on Multicore Embedded Systems

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