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Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems
<span title="">2015</span>
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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/t3x4vqewrncrfgn2wu7cafsbsq" style="color: black;">2015 IEEE International Parallel and Distributed Processing Symposium</a>
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In this work, we revisit the 1999 Gordon Bell Prize winning PETSc-FUN3D aerodynamics code, extending it with highly-tuned shared-memory parallelization and detailed performance analysis on modern highly parallel architectures. An unstructured-grid implicit flow solver, which forms the backbone of computational aerodynamics, poses particular challenges due to its large irregular working sets, unstructured memory accesses, and variable/limited amount of parallelism. This code, based on a domain
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... composition approach, exposes tradeoffs between the number of threads assigned to each MPI-rank subdomain, and the total number of domains. By applying several algorithmand architecture-aware optimization techniques for unstructured grids, we show a 6.9X speed-up in performance on a singlenode Intel R Xeon TM 1 E5 2690v2 processor relative to the outof-the-box compilation. Our scaling studies on TACC Stampede supercomputer show that our optimizations continue to provide performance benefits over baseline implementation as we scale up to 256 nodes.
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