alexa Test Harness on a Preconditioned Conjugate Gradient Solver on GPUs: An Efficiency Analysis


Journal of Information Technology & Software Engineering

Author(s): A Wendell de O Rodrigues, Loc Chevallier, Yvonnick Le Menach, Frdric Guyomarch

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The parallelization of numerical simulation algorithms, i.e., their adaptation to parallel processing architectures, is an aim to reach in order to hinder exorbitant execution times. The parallelism has been imposed at the level of processor architectures and graphics cards are now used for general-purpose calculation, also known as “General-Purpose computation on Graphics Processing Unit (GPGPU)”. The clear benefit is the excellent performance over price ratio. Besides hiding the low level programming, software engineering leads to a faster and more secure application development. This paper presents the real interest of using GPU processors to increase performance of larger problems which concern electrical machines simulation. Indeed, we show that our auto-generated code applied to several models allows achieving speedups of the order of 10 ×.

This article was published in IEEE Transactions on Magnetics and referenced in Journal of Information Technology & Software Engineering

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