DocumentCode
18453
Title
Cache Coherence for GPU Architectures
Author
Singh, Inderjit ; Shriraman, A. ; Fung, W.W.L. ; O´Connor, Mike ; Aamodt, T.M.
Volume
34
Issue
3
fYear
2014
fDate
May-June 2014
Firstpage
69
Lastpage
79
Abstract
GPUs have become an attractive target for accelerating parallel applications and delivering significant speedups and energy-efficiency gains over multicore CPUs. Programming GPUs, however, remains challenging because existing GPUs lack the well-defined memory model required to support high-level languages such as C++ and Java. The authors tackle this challenge with Temporal Coherence, a simple and intuitive timer-based coherence framework optimized for GPU.
Keywords
cache storage; energy conservation; graphics processing units; multiprocessing systems; parallel processing; GPU architectures; GPU programming; cache coherence; energy-efficiency gains; multicore CPU; parallel applications; temporal coherence; timer-based coherence framework; Cache memory; Computer architecture; Graphics processing units; Memory management; Message systems; Protocols; Cache memory; Computer architecture; GPU; Graphics processing units; Memory management; Message systems; Protocols; cache coherence; graphics processing unit; hardware; hardware/software interface; high performance computing; memory consistency models; parallel processors; software;
fLanguage
English
Journal_Title
Micro, IEEE
Publisher
ieee
ISSN
0272-1732
Type
jour
DOI
10.1109/MM.2014.4
Filename
6756705
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