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Porting of finite element integration algorithm to Xeon Phi coprocessor-based HPC architectures

Krużel Filip, Banaś Krzysztof, Iacomo Mauro

Computer Assisted Methods in Engineering and Science

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2023

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Vol. 30, no. 4

427--459

EN

In the present article, we describe the implementation of the finite element numerical integration algorithm for the Xeon Phi coprocessor. The coprocessor was an extension of the many-core specialized unit for calculations, and its performance was comparable with the corresponding GPUs. Its main advantages were the built-in 512-bit vector registers and the ease of transferring existing codes from traditional x86 architectures. In the article, we move the code developed for a standard CPU to the coprocessor. We compareits performance with our OpenCL implementation of the numerical integration algorithm, previously developed for GPUs. The GPU code is tuned to fit into a coprocessor by ourauto-tuning mechanism. Tests included two types of tasks to solve, using two types of approximation and two types of elements. The obtained timing results allow comparing the performance of highly optimized CPU and GPU codes with a Xeon Phi coprocessor performance. This article answers whether such massively parallel architectures perform better using the CPU or GPU programming method. Furthermore, we have compared the Xeon Phi architecture and the latest available Intel’s i9 13900K CPU when writing this article. This comparison determines if the old Xeon Phi architecture remains competitive in today’s computing landscape. Our findings provide valuable insights for selectingthe most suitable hardware for numerical computations and the appropriate algorithmic design.

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Intel Iris Xe-LP as a platform for scientific computing

Krużel Filip, Nytko Mateusz

Annals of Computer Science and Information Systems

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2022

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Vol. 32

121--128

EN

In the present article, we describe the implementation of the finite element numerical integration algorithm for the Intel Iris Xe-LP Graphics Processing Unit. This GPU is a direct successor of a Xeon Phi accelerator architecture. Although it is used in integrated circuits and does not offer substantial performance, its test should be treated as a preview of the estimated performance for the Intel HPG Graphics Cards that are announced to be released in 2022. In the article, we use our previously developed auto-tuning Finite Element numerical integration OpenCL code on the Intel Iris Xe-LP GPU integrated into the Intel i7 11370H CPU and compare the results with the Nvidia GeForce RTX 3060 GPU. This article brings the answer to the question of whether the new Intel architecture can be a direct competitor to the more classic GPU architecture. It also allows showing if the new architecture can be used for the computation of complex engineering tasks.

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Implementation of numerical integrationto high-order elements on the GPUs

Krużel Filip, Banaś Krzysztof, Nytko Mateusz

Computer Assisted Methods in Engineering and Science

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2020

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Vol. 27, no. 1

3--26

EN

This article presents ways to implement a resource-consuming algorithm on hardware with a limited amount of memory, which is the GPU. Numerical integration for higher-order finite element approximation was chosen as an example algorithm. To perform compu- tational tests, we use a non-linear geometric element and solve the convection-diffusion- reaction problem. For calculations, a Tesla K20m graphics card based on Kepler archi- tecture and Radeon r9 280X based on Tahiti XT architecture were used. The results of computational experiments were compared with the theoretical performance of both GPUs, which allowed an assessment of actual performance. Our research gives sugges- tions for choosing the optimal design of algorithms as well as the right hardware for such a resource-demanding task.