NDLI: Automatic communication optimizations through memory reuse strategies

Content Provider	ACM Digital Library
Author	Vasilache, Nicolas Baskaran, Muthu Manikandan Meister, Benoit Lethin, Richard
Abstract	Modern parallel architectures are emerging with sophisticated hardware consisting of hierarchically placed parallel processors and memories. The properties of memories in a system vary wildly, not only quantitatively (size, latency, bandwidth, number of banks) but also qualitatively (scratchpad, cache). Along with the emergence of such architectures comes the need for effectively utilizing the parallel processors and properly managing data movement across memories to improve memory bandwidth and hide data transfer latency. In this paper, we describe some of the high-level optimizations that are targeted at the improvement of memory performance in the R-Stream compiler, a high-level source-to-source automatic parallelizing compiler. We direct our focus in this paper on optimizing communications (data transfers) by improving memory reuse at various levels of an explicit memory hierarchy. This general concept is well-suited to the hardware properties of GPGPUs, which is the architecture that we concentrate on for this paper. We apply our techniques and obtain performance improvement on various stencil kernels including an important iterative stencil kernel in seismic processing applications where the performance is comparable to that of the state-of-the-art implementation of the kernel by a CUDA expert.
Starting Page	277
Ending Page	278
Page Count	2
File Format	PDF
ISSN	03621340 15581160
DOI	10.1145/2370036.2145852
Journal	ACM SIGPLAN Notices (SIGP)
Volume Number	47
Issue Number	8
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1983-05-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Data transfer optimization Memory reuse Data reuse
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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