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Cache Coherence for GPU Architectures
Author(s) -
Inderpreet Singh,
Arrvindh Shriraman,
Wilson W.L. Fung,
Mike O'Connor,
Tor M. Aamodt
Publication year - 2014
Publication title -
ieee micro
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.649
H-Index - 94
eISSN - 1937-4143
pISSN - 0272-1732
DOI - 10.1109/mm.2014.4
Subject(s) - computing and processing
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.

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