This paper presents PAMPAR, a new benchmark to evaluate the performance and energy consumption of different Parallel Programming Interfaces (PPIs). The benchmark is composed of 11 algorithms implemented in PThreads, OpenMP, MPI-1, and MPI-2 (spawn) PPIs. Previous studies have used some of these pseudo-applications to perform this type of evaluation in different architectures since there is no benchmark that offers this variety of PPIs and communication models. In this work, we measure the energy and performance of each pseudo-application in a single architecture, varying the number of threads/processes. We also organize the pseudo-applications according to their memory accesses, floating-point operations, and branches. The goal is to show that this set of pseudo-applications has enough features to build a parallel benchmark. The results show that there is no single best case that provides both better performance and low energy consumption in the presented scenarios. Moreover, the pseudo-applications usage of the system resources are different enough to represent different scenarios and be efficient as a benchmark.
PAMPAR: A new parallel benchmark for performance and energy consumption evaluation
Adriano Marques Garcia
First
;
2020-01-01
Abstract
This paper presents PAMPAR, a new benchmark to evaluate the performance and energy consumption of different Parallel Programming Interfaces (PPIs). The benchmark is composed of 11 algorithms implemented in PThreads, OpenMP, MPI-1, and MPI-2 (spawn) PPIs. Previous studies have used some of these pseudo-applications to perform this type of evaluation in different architectures since there is no benchmark that offers this variety of PPIs and communication models. In this work, we measure the energy and performance of each pseudo-application in a single architecture, varying the number of threads/processes. We also organize the pseudo-applications according to their memory accesses, floating-point operations, and branches. The goal is to show that this set of pseudo-applications has enough features to build a parallel benchmark. The results show that there is no single best case that provides both better performance and low energy consumption in the presented scenarios. Moreover, the pseudo-applications usage of the system resources are different enough to represent different scenarios and be efficient as a benchmark.File | Dimensione | Formato | |
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