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dc.contributor.authorAl Farhan, Mohammed
dc.contributor.authorKaushik, Dinesh K.
dc.contributor.authorKeyes, David E.
dc.date.accessioned2017-05-04T12:33:23Z
dc.date.available2017-05-04T12:33:23Z
dc.date.issued2017-03-13
dc.identifier.urihttp://hdl.handle.net/10754/623355
dc.description.abstractShared memory parallelization of PETSc-FUN3D, an unstructured tetrahedral mesh Euler code previously characterized for distributed memory Single Program, Multiple Data (SPMD) for thousands of nodes, is hybridized with shared memory Single Instruction, Multiple Data (SIMD) for hundreds of threads per node. We explore thread-level performance optimizations on state-of-the-art multi- and many-core Intel processors, including the second generation of Xeon Phi, Knights Landing (KNL). We study the performance on the KNL with different configurations of memory and cluster modes, with code optimizations to minimize indirect addressing and enhance the cache locality. The optimizations employed are expected to be of value other unstructured applications as many-core architecture evolves.
dc.titleImplicit Unstructured Aerodynamics on Emerging Multi- and Many-Core HPC Architectures
dc.typePoster
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentExtreme Computing Research Center
dc.conference.dateMarch 13-15, 2017
dc.conference.nameHigh Performance Computing Saudi Arabia (HPC Saudi) 2017
dc.conference.locationKAUST
dc.contributor.institutionQatar Environment and Energy Research Institute
kaust.personAl Farhan, Mohammed
kaust.personKeyes, David E.
refterms.dateFOA2018-06-13T16:22:36Z


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