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Nekbone performance on GPUs with OpenACC and CUDA Fortran implementations
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC. KTH, Centra, SeRC - Swedish e-Science Research Centre.ORCID-id: 0000-0002-3859-9480
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC.ORCID-id: 0000-0003-0639-0639
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC.ORCID-id: 0000-0002-9901-9857
Vise andre og tillknytning
2016 (engelsk)Inngår i: Journal of Supercomputing, ISSN 0920-8542, E-ISSN 1573-0484, Vol. 72, nr 11, s. 4160-4180Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We present a hybrid GPU implementation and performance analysis of Nekbone, which represents one of the core kernels of the incompressible Navier-Stokes solver Nek5000. The implementation is based on OpenACC and CUDA Fortran for local parallelization of the compute-intensive matrix-matrix multiplication part, which significantly minimizes the modification of the existing CPU code while extending the simulation capability of the code to GPU architectures. Our discussion includes the GPU results of OpenACC interoperating with CUDA Fortran and the gather-scatter operations with GPUDirect communication. We demonstrate performance of up to 552 Tflops on 16, 384 GPUs of the OLCF Cray XK7 Titan.

sted, utgiver, år, opplag, sider
Springer, 2016. Vol. 72, nr 11, s. 4160-4180
Emneord [en]
Nekbone/Nek5000, OpenACC, CUDA Fortran, GPUDirect, Gather-scatter communication, Spectral element discretization
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-198970DOI: 10.1007/s11227-016-1744-5ISI: 000387234200007Scopus ID: 2-s2.0-84978656496OAI: oai:DiVA.org:kth-198970DiVA, id: diva2:1065628
Forskningsfinansiär
Swedish e‐Science Research Center
Merknad

QC 20170116

Tilgjengelig fra: 2017-01-16 Laget: 2016-12-22 Sist oppdatert: 2017-08-16bibliografisk kontrollert

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Gong, JingMarkidis, StefanoLaure, Erwin

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