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
Link To Document :
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