Advances in CUDA for computational physics

Authors

  • Delia Spiridon Transilvania University of Brasov, Romania

DOI:

https://doi.org/10.31926/but.mif.2023.3.65.2.19

Keywords:

parallel programming, computational physics

Abstract

Advances in the graphics processing unit (GPU) development led to the opportunity for software developers to increase the execution speed for their programs by massive parallelization of the algorithms using GPU programming. NVIDIA company developed an arhitecture for parallel computing named Compute Unified Device Architecture (CUDA) which includes a set of CUDA instructions and the hardware for parallel computing. Computational Physics is an interdisciplinary field which is in continuous progress and which studies, develops and optimizes numerical algorithms and computational techniques for their application in solving various physics problems. Computational Physics has applicability in all sub-branches of physics and related fields such as: biophysics, astrophysics, plasma physics, biomechanics, fluid physics, etc. Moreover, with the evolution of technology in the last few decades, this relatively new field has helped to quickly obtain results in these fields, facilitating the connection between theoretical and experimental physics. In this paper, some of the latest researches and results obtained in computational physics by using GPU computing with CUDA architecture are reviewed.

Author Biography

Delia Spiridon, Transilvania University of Brasov, Romania

Faculty of Mathematics and Informatics

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Published

2023-12-18

Issue

Section

COMPUTER SCIENCE