@inproceedings{1047d8fcf30346e6a23dfef79aed04bc,
title = "Automatic CPU-GPU communication management and optimization",
abstract = "The performance benefits of GPU parallelism can be enormous, but unlocking this performance potential is challenging. The applicability and performance of GPU parallelizations is limited by the complexities of CPU-GPU communication. To address these communications problems, this paper presents the first fully automatic system for managing and optimizing CPU-GPU communcation. This system, called the CPU-GPU Communication Manager (CGCM), consists of a run-time library and a set of compiler transformations that work together to manage and optimize CPU-GPU communication without depending on the strength of static compile-time analyses or on programmer-supplied annotations. CGCM eases manual GPU parallelizations and improves the applicability and performance of automatic GPU parallelizations. For 24 programs, CGCM-enabled automatic GPU parallelization yields a whole program geomean speedup of 5.36x over the best sequential CPU-only execution.",
keywords = "communication, gpu, management, optimization",
author = "Jablin, {Thomas B.} and Prakash Prabhu and Jablin, {James A.} and Johnson, {Nick P.} and Beard, {Stephen R.} and August, {David I.}",
year = "2011",
doi = "10.1145/1993498.1993516",
language = "English (US)",
isbn = "9781450306638",
series = "Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)",
pages = "142--151",
booktitle = "PLDI'11 - Proceedings of the 2011 ACM Conference on Programming Language Design and Implementation",
note = "32nd ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI'11 ; Conference date: 04-06-2011 Through 08-06-2011",
}