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2014 23rd International Conference on Parallel Architecture and Compilation (PACT) (2014)
Edmonton, Canada
Aug. 23, 2014 to Aug. 27, 2014
ISBN: 978-1-5090-6607-0
pp: 515-516
Thomas R. W. Scogland , Virginia Tech
Wu-Chun Feng , Virginia Tech
ABSTRACT
Heterogeneity is an ever-growing challenge in computing. The clearest example is the increasing popularity of GPUs, and purpose-designed coprocessors such as Intel Xeon Phi. Even disregarding coprocessors, heterogeneity continues to increase with the rise in CPU core counts, adaptive per-core frequencies, and increasingly hierarchical and complex memory systems. Take a system with four memory nodes, associated with four cores each, and four GPUs, each with a distinct address space and tens to hundreds of cores pro­grammed like a bulk-synchronous parallel cluster. In this case, we are effectively programming clusters of miniature constellations in every node.
INDEX TERMS
Adaptive systems, Graphics processing units, Runtime, Optimization, Coprocessors, Programming, Layout
CITATION
Thomas R. W. Scogland, Wu-Chun Feng, "Locality-aware memory association for multi-target worksharing in OpenMP", 2014 23rd International Conference on Parallel Architecture and Compilation (PACT), vol. 00, no. , pp. 515-516, 2014, doi:10.1145/2628071.2671428
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