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Performance Analysis of Modern Parallel Programming Models for GPUs: OpenMP, OpenACC, CUDA

Student: Mikhail Khalilov

Supervisor: Alexey Timofeev

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Mathematical Methods of Modelling and Computer Technologies (Master)

Final Grade: 10

Year of Graduation: 2020

Modern supercomputers use graphics processors as accelerators in compute nodes. GPUs enable scientific applications to significantly increase performance using fine-grained parallelism. The CUDA programming model focuses on optimized use of the SIMT architecture by writing low-level C/C++ code. At the same time, OpenACC and OpenMP 4.5 are part of the family of declarative parallel programming models. This study compares the effectiveness of the CUDA, OpenACC, and OpenMP programming models for various tests. The analysis of the GPU memory performance, the performance of physical tasks and various matrix multiplication implementations on Nvidia Tesla V100 and MX940 GPUs and modern processors is presented.

Full text (added May 17, 2020)

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