Strategies to parallelize a finite element mesh truncation technique on multi-core and many-core architectures

Autor: Jose M. Badia, Adrian Amor-Martin, Jose A. Belloch, Luis Emilio Garcia-Castillo
Přispěvatelé: Comunidad de Madrid, Ministerio de Ciencia e Innovación (España)
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Popis: Achieving maximum parallel performance on multi-core CPUs and many-core GPUs is a challenging task depending on multiple factors. These include, for example, the number and granularity of the computations or the use of the memories of the devices. In this paper, we assess those factors by evaluating and comparing different parallelizations of the same problem on a multiprocessor containing a CPU with 40 cores and four P100 GPUs with Pascal architecture. We use, as study case, the convolutional operation behind a non-standard finite element mesh truncation technique in the context of open region electromagnetic wave propagation problems. A total of six parallel algorithms implemented using OpenMP and CUDA have been used to carry out the comparison by leveraging the same levels of parallelism on both types of platforms. Three of the algorithms are presented for the first time in this paper, including a multi-GPU method, and two others are improved versions of algorithms previously developed by some of the authors. This paper presents a thorough experimental evaluation of the parallel algorithms on a radar cross-sectional prediction problem. Results show that performance obtained on the GPU clearly overcomes those obtained in the CPU, much more so if we use multiple GPUs to distribute both data and computations. Accelerations close to 30 have been obtained on the CPU, while with the multi-GPU version accelerations larger than 250 have been achieved. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work has been supported by the Spanish Government PID2020-113656RB-C21, PID2019-106455GB-C21 and by the Valencian Regional Government through PROMETEO/2019/109, as well as the Regional Government of Madrid throughout the project MIMACUHSPACE-CM-UC3M.
Databáze: OpenAIRE