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From Serial Loops to Parallel Execution on Distributed Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7484)

Abstract

Programmability and performance portability are two major challenges in today’s dynamic environment. Algorithm designers targeting efficient algorithms should focus on designing high-level algorithms exhibiting maximum parallelism, while relying on compilers and run-time systems to discover and exploit this parallelism, delivering sustainable performance on a variety of hardware. The compiler tool presented in this paper can analyze the data flow of serial codes with imperfectly nested, affine loop-nests and if statements, commonly found in scientific applications. This tool operates as the front-end compiler for the DAGuE run-time system by automatically converting serial codes into the symbolic representation of their data flow. We show how the compiler analyzes the data flow, and demonstrate that scientifically important, dense linear algebra operations can benefit from this analysis, and deliver high performance on large scale platforms.

Keywords

compiler analysis symbolic data flow distributed computing task scheduling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.University of TennesseeKnoxvilleUSA
  2. 2.University of ManchesterManchesterUK

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