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Offloading C++17 Parallel STL on System Shared Virtual Memory Platforms

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Original languageEnglish
Title of host publicationHigh Performance Computing
Subtitle of host publicationISC High Performance 2018 International Workshops, Frankfurt/Main, Germany, June 24 - 28, 2018, Revised Selected Papers
ISBN (Electronic)978-3-030-02465-9
Publication statusPublished - 28 Jun 2018
Publication typeA4 Article in a conference publication
EventISC High Performance International Workshops -
Duration: 28 Jun 201828 Jun 2018

Publication series

NameTheoretical Computer Science and General Issues
ISSN (Print)0302-9743


ConferenceISC High Performance International Workshops


Shared virtual memory simplifies heterogeneous platform programming by enabling sharing of memory address pointers between heterogeneous devices in the platform. The most advanced implementations present a coherent view of memory to the programmer over the whole virtual address space of the process. From the point of view of data accesses, this System SVM (SSVM) enables the same programming paradigm in heterogeneous platforms as found in homogeneous platforms. C++ revision 17 adds its first features for explicit parallelism through its “Parallel Standard Template Library” (PSTL). This paper discusses the technical issues in offloading PSTL on heterogeneous platforms supporting SSVM and presents a working GCC-based proof-of-concept implementation. Initial benchmarking of the implementation on an AMD Carrizo platform shows speedups from 1.28X to 12.78X in comparison to host-only sequential STL execution.

Publication forum classification

Field of science, Statistics Finland

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