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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom