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Lost in heterogeneity: architectural selection based on code features

Published: 15 November 2015 Publication History

Abstract

Automatic parallelizing compilers have evolved greatly over the last decade. Tools like Pluto, Pr4All and PPCG are widely adopted to generate optimized OpenMP, CUDA and OpenCL codes. However, in the end, it is the programmer's responsibility to select the best target architecture for a particular application. In this work we provide a solution for the problem of architectural selection. We introduce a low cost model based on a classification problem which selects the fastest architecture for the generated code. We integrate our model in PPCG, a state of the art polyhedral compiler. Our experiments show that our model selects the fastest architecture 87% of the time when choosing between an Ivy Bridge Xeon CPU and a Kepler GPU and 81% of the time when choosing between a Xeon Sandy Bridge CPU and a Xeon Phi acceleration card.

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cover image ACM Conferences
Co-HPC '15: Proceedings of the 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing
November 2015
61 pages
ISBN:9781450339926
DOI:10.1145/2834899
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 November 2015

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Co-HPC '15 Paper Acceptance Rate 7 of 13 submissions, 54%;
Overall Acceptance Rate 7 of 13 submissions, 54%

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