Offloading C++17 Parallel STL on System Shared Virtual Memory Platforms
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | High Performance Computing |
| Subtitle of host publication | ISC High Performance 2018 International Workshops, Frankfurt/Main, Germany, June 24 - 28, 2018, Revised Selected Papers |
| Publisher | Springer |
| Pages | 637-647 |
| ISBN (Electronic) | 978-3-030-02465-9 |
| Publication status | Published - 28 Jun 2018 |
| Publication type | A4 Article in a conference publication |
| Event | ISC High Performance International Workshops - Duration: 28 Jun 2018 → 28 Jun 2018 |
Publication series
| Name | Theoretical Computer Science and General Issues |
|---|---|
| Volume | 11203 |
| ISSN (Print) | 0302-9743 |
Conference
| Conference | ISC High Performance International Workshops |
|---|---|
| Period | 28/06/18 → 28/06/18 |
Abstract
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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