GPU libraries speed performance analysis for RCWA simulation matrix operations
Proceedings of SPIE - The International Society for Optical Engineering
; 12415, 2023.
Artigo
em Inglês
| Scopus | ID: covidwho-20244908
ABSTRACT
Rigorous Coupled Wave Analysis (RCWA) method is highly efficient for the simulation of diffraction efficiency and field distribution patterns in periodic structures and textured optoelectronic devices. GPU has been increasingly used in complex scientific problems such as climate simulation and the latest Covid-19 spread model. In this paper, we break down the RCWA simulation problem to key computational steps (eigensystem solution, matrix inversion/multiplication) and investigate speed performance provided by optimized linear algebra GPU libraries in comparison to multithreaded Intel MKL CPU library running on IRIDIS 5 supercomputer (1 NVIDIA v100 GPU and 40 Intel Xeon Gold 6138 cores CPU). Our work shows that GPU outperforms CPU significantly for all required steps. Eigensystem solution becomes 60% faster, Matrix inversion improves with size achieving 8x faster for large matrixes. Most significantly, matrix multiplication becomes 40x faster for small and 5x faster for large matrix sizes. © 2023 SPIE.
eigensystem; GPU computing; Matrix operation; MKL library; RCWA; Graphics processing unit; Matrix algebra; Optoelectronic devices; Supercomputers; Textures; Analysis method; Matrix inversions; Matrix operations; Performances analysis; Simulation matrices; Speed performance; The rigorous coupledwave analyses (RCWA); Libraries
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Coleções:
Bases de dados de organismos internacionais
Base de dados:
Scopus
Idioma:
Inglês
Revista:
Proceedings of SPIE - The International Society for Optical Engineering
Ano de publicação:
2023
Tipo de documento:
Artigo
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