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Parallel Programming with Inductive Synthesis

By Shaon Barman, Rastislav Bodik, Sagar Jain, Yewen Pu, Saurabh Srivastava and Nicholas Tung

Abstract

We show that program synthesis can generate GPU algorithms as well as their optimized implementations. Using the scan kernel as a case study, we describe our evolving synthesis techniques. Relying on our synthesizer, we can parallelize a serial problem by transforming it into a scan operation, synthesize a SIMD scan algorithm, and optimize it to reduce memory conflicts. 1 The Problem Parallel codes are almost exclusively hand-written. Their coding is time-consuming in part for these reasons: • Need for new algorithms. To map a problem to hardware, we may need a new algorithm. For example, by reformulating a serial problem as a prefix sum, we can solve it on data-parallel architectures

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.363.6611
Provided by: CiteSeerX
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