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A compiler and runtime for heterogeneous computing

Authors:

Sunil ShuklaAuthors Info & Claims

DAC '12: Proceedings of the 49th Annual Design Automation Conference

Pages 271 - 276

https://doi.org/10.1145/2228360.2228411

Published: 03 June 2012 Publication History

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Abstract

Heterogeneous systems show a lot of promise for extracting high-performance by combining the benefits of conventional architectures with specialized accelerators in the form of graphics processors (GPUs) and reconfigurable hardware (FPGAs). Extracting this performance often entails programming in disparate languages and models, making it hard for a programmer to work equally well on all aspects of an application. Further, relatively little attention is paid to co-execution---the problem of orchestrating program execution using multiple distinct computational elements that work seamlessly together.

We present Liquid Metal, a comprehensive compiler and runtime system for a new programming language called Lime. Our work enables the use of a single language for programming heterogeneous computing platforms, and the seamless co-execution of the resultant programs on CPUs and accelerators that include GPUs and FPGAs.

We have developed a number of Lime applications, and successfully compiled some of these for co-execution on various GPU and FPGA enabled architectures. Our experience so far leads us to believe the Liquid Metal approach is promising and can make the computational power of heterogeneous architectures more easily accessible to mainstream programmers.

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Cited By

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Majumder KBondhugula UAamodt TSwift MJerger N(2023)HIR: An MLIR-based Intermediate Representation for Hardware Accelerator DescriptionProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 410.1145/3623278.3624767(189-201)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3623278.3624767
Mack JHassan SKumbhare NCastro Gonzalez MAkoglu A(2023)CEDR: A Compiler-integrated, Extensible DSSoC RuntimeACM Transactions on Embedded Computing Systems10.1145/352925722:2(1-34)Online publication date: 24-Jan-2023
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Ahangari HÖzdal MÖztürk Ö(2023)HLS-based High-throughput and Work-efficient Synthesizable Graph Processing Template PipelineACM Transactions on Embedded Computing Systems10.1145/352925622:2(1-24)Online publication date: 24-Jan-2023
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Index Terms

A compiler and runtime for heterogeneous computing
1. Hardware
  1. Integrated circuits
    1. Logic circuits
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language features

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Published In

DAC '12: Proceedings of the 49th Annual Design Automation Conference

June 2012

1357 pages

ISBN:9781450311991

DOI:10.1145/2228360

General Chair:
Patrick Groeneveld
Magma Design Automation, Inc., San Jose, CA
,
Program Chairs:
Donatella Sciuto
Politecnico di Milano, Milano, Italy
,
Soha Hassoun
Tufts Univ., Medford, MA

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: 03 June 2012

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DAC '12: The 49th Annual Design Automation Conference 2012

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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https://dl.acm.org/doi/10.1145/3623278.3624767
Mack JHassan SKumbhare NCastro Gonzalez MAkoglu A(2023)CEDR: A Compiler-integrated, Extensible DSSoC RuntimeACM Transactions on Embedded Computing Systems10.1145/352925722:2(1-34)Online publication date: 24-Jan-2023
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Ahangari HÖzdal MÖztürk Ö(2023)HLS-based High-throughput and Work-efficient Synthesizable Graph Processing Template PipelineACM Transactions on Embedded Computing Systems10.1145/352925622:2(1-24)Online publication date: 24-Jan-2023
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Adaptive Optimization for Petascale Heterogeneous CPU/GPU Computing

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Adaptive Optimization for Petascale Heterogeneous CPU/GPU Computing

The RACECAR heuristic for automatic function specialization on multi-core heterogeneous systems

Offload Compiler Runtime for the Intel® Xeon Phi Coprocessor

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