Task based Cholesky decomposition on Xeon Phi architectures using OpenMP
by Joseph Dorris; Asim YarKhan; Jakub Kurzak; Piotr Luszczek; Jack Dongarra
International Journal of Computational Science and Engineering (IJCSE), Vol. 17, No. 3, 2018

Abstract: The increasing number of computational cores in modern many-core processors, as represented by the Intel Xeon Phi architectures, has created the need for an open-source, high performance and scalable task-based dense linear algebra package that can efficiently use this type of many-core hardware. In this paper, we examined the design modifications necessary when porting PLASMA, a task-based dense linear algebra library, run effectively on two generations of Intel's Xeon Phi architecture, known as knights corner (KNC) and knights landing (KNL). First, we modified PLASMA's tiled Cholesky decomposition to use OpenMP tasks for its scheduling mechanism to enable Xeon Phi compatibility. We then compared the performance of our modified code to that of the original dynamic scheduler running on an Intel Xeon Sandy Bridge CPU. Finally, we looked at the performance of the OpenMP tiled Cholesky decomposition on knights corner and knights landing processors. We detail the optimisations required to obtain performance on these platforms and compare with the highly tuned Intel MKL math library.

Online publication date: Mon, 22-Oct-2018

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