Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems

Dheevatsa Mudigere, Srinivas Sridharan, Anand Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh Kaushik, David Keyes
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/t3x4vqewrncrfgn2wu7cafsbsq" style="color: black;">2015 IEEE International Parallel and Distributed Processing Symposium</a> </i> &nbsp;
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
more &raquo; ... 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ipdps.2015.114">doi:10.1109/ipdps.2015.114</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ipps/MudigereSDPHSKD15.html">dblp:conf/ipps/MudigereSDPHSKD15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fajgerf4zfgtnb2l2wafdnd27y">fatcat:fajgerf4zfgtnb2l2wafdnd27y</a> </span>
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