ACCELERATING COMPUTATIONAL FLUID DYNAMICS CODES ON MULTI-/MANY-CORE INTEL PLATFORMS

Gaurav Bansal, Anand Deshpande, Paul Edwards, Alexander Heinecke, Michael Klemm, Dheevatsa Mudigere, Elmoustapha Ould-Ahmed-Vall, Mikhail Smelyanskiy, Michael Steyer, Nishant Agrawal, Ravi Ojha, Ambuj Pandey (+5 others)
unpublished
In this paper, we present optimization techniques that are crucial to unlock parallelism and vectorization in modern computational fluid dynamics (CFD) codes thereby significantly improving their performance on emerging Intel multi-/many-core platforms such as the Intel R Xeon R 1 processors and Intel R Xeon Phi TM1 coprocessors. We focus on unstructured-mesh finite-volume codes and restrict the discussion to fine-scale optimizations with the objective to improve the strong-scaling behavior of
more » ... hese classes of algorithms. We present the key architectural features of the Intel Xeon Phi coprocessor and describe strategies to exploit them for improving performance of three widely used CFD codes. Our benchmarking results show substantial performance advantages to speed up time-to-solution.
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