Improving application behavior on heterogeneous manycore systems through kernel mapping

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dc.citation.epage878en_US
dc.citation.issueNumber12en_US
dc.citation.spage867en_US
dc.citation.volumeNumber39en_US
dc.contributor.authorAlbayrak, O. E.en_US
dc.contributor.authorAkturk, I.en_US
dc.contributor.authorOzturk, O.en_US
dc.date.accessioned2016-02-08T12:04:24Z
dc.date.available2016-02-08T12:04:24Z
dc.date.issued2013en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractMany-core accelerators are being more frequently deployed to improve the system processing capabilities. In such systems, application mapping must be enhanced to maximize utilization of the underlying architecture. Especially, in graphics processing units (GPUs), mapping kernels that are part of multi-kernel applications has a great impact on overall performance, since kernels may exhibit different characteristics on different CPUs and GPUs. While some kernels run faster on GPUs, others may perform better in CPUs. Thus, heterogeneous execution may yield better performance than executing the application only on a CPU or only on a GPU. In this paper, we investigate on two approaches: a novel profiling-based adaptive kernel mapping algorithm to assign each kernel of an application to the proper device, and a Mixed-Integer Programming (MIP) implementation to determine optimal mapping. We utilize profiling information for kernels on different devices and generate a map that identifies which kernel should run where in order to improve the overall performance of an application. Initial experiments show that our approach can efficiently map kernels on CPUs and GPUs, and outperforms CPU-only and GPU-only approaches. © 2013 Elsevier B.V. All rights reserved.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T12:04:24Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2013en
dc.identifier.doi10.1016/j.parco.2013.08.011en_US
dc.identifier.issn0167-8191
dc.identifier.urihttp://hdl.handle.net/11693/27902
dc.language.isoEnglishen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.parco.2013.08.011en_US
dc.source.titleParallel Computing: systems & applicationsen_US
dc.subjectKernel mappingen_US
dc.subjectMixed integer programmingen_US
dc.subjectGraphics processing unitsen_US
dc.subjectHeterogeneous many coresen_US
dc.subjectHeterogeneous systemsen_US
dc.subjectMany - core acceleratorsen_US
dc.subjectProfiling informationsen_US
dc.subjectComputer graphicsen_US
dc.subjectConformal mappingen_US
dc.subjectEmbedded systemsen_US
dc.subjectInteger programmingen_US
dc.subjectProgram processorsen_US
dc.titleImproving application behavior on heterogeneous manycore systems through kernel mappingen_US
dc.typeArticleen_US

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