Pushing the Limits of the Maya Cluster

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dc.contributor.authorCunningham, Adam
dc.contributor.authorPayton, Gerald
dc.contributor.authorSlettebak, Jack
dc.contributor.authorPou, Jordi Wolfson
dc.contributor.authorGraf, Jonathan
dc.contributor.authorHuang, Xuan
dc.contributor.authorKhuvis, Samuel
dc.contributor.authorGobbert, Matthias K.
dc.contributor.authorSalter, Thomas
dc.contributor.authorMountain, David J.
dc.date.accessioned2018-10-01T13:47:04Z
dc.date.available2018-10-01T13:47:04Z
dc.date.issued2014
dc.description.abstractParallelization of code, using multiple cores/threads, and heterogeneous computing, using the CPU with other devices, has come to the forefront of computing as methods to reduce the execution time of computationally demanding algorithms. For our project, we test various hardware setups on the maya cluster at UMBC, which include multiple nodes and GPUs, by solving the Poisson equation using the conjugate gradient method. To explore these different setups, we made use of both industry benchmarks and our own code, which we design using the compilers native to each device and API. We fi nd significant gains both in using a heterogeneous model and after parallelizing our code.en_US
dc.description.sponsorshipThese results were obtained as part of the REU Site: Interdisciplinary Program in High Performance Computing (www.umbc.edu/hpcreu) in the Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC) in Summer 2014. This program is funded jointly by the National Science Foundation and the National Security Agency (NSF grant no. DMS{1156976), with additional support from UMBC, the Department of Mathematics and Statistics, the Center for Interdisciplinary Research and Consulting (CIRC), and the UMBC High Performance Computing Facility (HPCF). HPCF is supported by the U.S. National Science Foundation through the MRI program (grant nos. CNS{0821258 and CNS{1228778) and the SCREMS program (grant no. DMS{0821311), with additional substantial support from UMBC. Co-authors Adam Cunningham, Gerald Payton, and Jack Slettebak were supported, in part, by the UMBC National Security Agency (NSA) Scholars Program through a contract with the NSA. Co-authors Jonathan Graf, Xuan Huang, and Samuel Khuvis were supported during Summer 2014 by UMBC.en_US
dc.description.urihttps://userpages.umbc.edu/~gobbert/papers/REU2014Team4.pdfen_US
dc.format.extent20 pagesen_US
dc.genretechnical reporten_US
dc.identifierdoi:10.13016/M2MW28J4C
dc.identifier.urihttp://hdl.handle.net/11603/11406
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Mathematics Department Collection
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofseriesHPCF Technical Report;HPCF-2014-14
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectheterogeneous computingen_US
dc.subjectGPUsen_US
dc.subjectconjugate gradient methoden_US
dc.subjectParallelizationen_US
dc.subjectUMBC High Performance Computing Facility (HPCF)en_US
dc.subjectmultiple cores/threads
dc.subjectparallel computing code
dc.subjectPoisson equation
dc.titlePushing the Limits of the Maya Clusteren_US
dc.typeTexten_US

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