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Raising the level of many-core programming with compiler technology: meeting a grand challenge

Published: 11 September 2010 Publication History

Abstract

Modern GPUs and CPUs are massively parallel, many-core processors. While application developers for these many-core chips are reporting 10X-100X speedup over sequential code on traditional microprocessors, the current practice of many-core programming based on OpenCL, CUDA, and OpenMP puts strain on software development, testing and support teams. According to the semiconductor industry roadmap, these processors could scale up to over 1,000X speedup over single cores by the end of the year 2016. Such a dramatic performance difference between parallel and sequential execution will motivate an increasing number of developers to parallelize their applications. Today, an application programmer has to understand the desirable parallel programming idioms, manually work around potential hardware performance pitfalls, and restructure their application design in order to achieve their performance objectives on many-core processors. In this presentation, I will discuss why advanced compiler functionalities have not found traction with the developer communities, what the industry is doing today to try to address the challenges, and how the academic community can contribute to this exciting revolution.

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Published In

cover image ACM Conferences
PACT '10: Proceedings of the 19th international conference on Parallel architectures and compilation techniques
September 2010
596 pages
ISBN:9781450301787
DOI:10.1145/1854273

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 September 2010

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  1. many-core processors
  2. parallel programming

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  • Keynote

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PACT '10
Sponsor:
  • IFIP WG 10.3
  • IEEE CS TCPP
  • SIGARCH
  • IEEE CS TCAA

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Overall Acceptance Rate 121 of 471 submissions, 26%

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