Towards a benchmark for performance and power consumption evaluation of parallel programming interfaces

• Ano de defesa: 2019
• Autor(a) principal: Garcia, Adriano Marques
• Orientador(a): Girardi, Alessandro Gonçalves
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal do Pampa
• Programa de Pós-Graduação: Mestrado Acadêmico em Engenharia Elétrica
• Departamento: Campus Alegrete
• País: Brasil
• Palavras-chave em Português: Engenharia elétrica; Benchmarks; Consumo de energia elétrica; Electric power consumption
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS
• Link de acesso: https://dspace.unipampa.edu.br/jspui/handle/riu/4136

This wor k presents a set of pseudo-applications and proposes them to be used as a benchmar k to evaluate the perfor mance and power consumption of different Parallel Programming Interfaces (PPIs). The set consists of 11 algor ithms implemented in PThreads, OpenMP, MPI-1, and MPI-2 (spawn) PPIs. These PPIs were chosen because they are compatible with most of the current multi-core architectures. Previous studies have used some of these pseudo-applications to perfor m this type of evaluation in different architectures since there is no benchmar k that offers this var iety of PPIs and communication models. Recent related wor k that compare PPIs have looked for different alter natives to solve the problem since the available parallel benchmar ks do not meet this demand. The goal of this wor k is to propose the use of these pseudo-applications as a benchmar k to evaluate the perfor mance and power consumption of different PPIs. To achieve this goal, we analyze the behavior of pseudo-applications and PPIs with respect to cache access, branches, and floating point operations. The results of these exper iments showed that there is a good balance among pseudo-applications that make more or less intensive use of these parameters. In addition, we conducted a case study to evaluate the perfor mance, energy consumption, and power consumption (power dissipation) of these pseudo-applications. The results show that the pseudo-applications generally have a good perfor mance. Although the total energy consumption is, in some cases, 300 times greater among different MPI pseudo-applications, this difference does not appear in the power consumption. The PPIs and the pseudo-applications presented to use the hardware resources in a ver y dynamic way and our results show that they are able to represent different scenar ios. Therefore they can be used as a parallel benchmar k. Keywords: benchmark, performance, energy consumption.