NDLI: A compiler for high performance computing with many-core accelerators

Content Provider	IEEE Xplore Digital Library
Author	Nakasato, N. Makino, J.
Copyright Year	2009
Description	Author affiliation: National Astronomical Observatory of Japan (Makino, J.) \|\| University of Aizu, Department of Computer Science and Engineering (Nakasato, N.)
Abstract	We introduce a newly developed compiler for high performance computing using many-core accelerators. A high peak performance of such accelerators attracts researchers who are always demanding faster computers. However, it is difficult to create an efficient implementation of an existing serial program for such accelerators even in the case of massively parallel problems. While existing parallel programming tools force us to program every details of an implementation from loop-level parallelism to 4-vector SIMD operations, our novel approach is that given a compute intensive problem expressed as a nested loop, the compiler only ask us to define a compute kernel inside the inner-most loop. We observe that input variables appeared in the kernel is classified into two types; invariant during the loop and variables updated in each iteration. The compiler let us to specify either type of the inputs so as it pick a predefined optimal way to process them. The compiler successfully generates the fastest code ever for many-particle simulations with the performance of 500 GFLOPS (single precision) on RV770 GPU. Another successful application is the evaluation of a multidimensional integral. It runs at a speed of 5–7 GFLOPS (quadruple precision) on both GRAPE-DR and GPU.
Starting Page	1
Ending Page	9
File Size	142023
Page Count	9
File Format	PDF
ISBN	9781424450114
ISSN	15525244
DOI	10.1109/CLUSTR.2009.5289127
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	High performance computing Acceleration Concurrent computing Kernel Parallel programming Parallel processing Program processors Input variables Multidimensional systems Pipelines
Content Type	Text
Resource Type	Article

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