research-article

A MATLAB Vectorizing Compiler Targeting Application-Specific Instruction Set Processors

Authors:

Ioannis Latifis,

Karthick Parashar,

Grigoris Dimitroulakos,

Christakis Lezos,

Konstantinos Masselos,

Francky CatthoorAuthors Info & Claims

ACM Transactions on Design Automation of Electronic Systems (TODAES), Volume 22, Issue 2

Article No.: 32, Pages 1 - 28

https://doi.org/10.1145/2996182

Published: 04 January 2017 Publication History

Abstract

This article discusses a MATLAB-to-C vectorizing compiler that exploits custom instructions, for example, for Single Instruction Multiple Data (SIMD) processing and instructions for complex arithmetic present in Application-Specific Instruction Set Processors (ASIPs). Custom instructions are represented via specialized intrinsic functions in the generated code, and the generated code can be used as input to any C/C++ compiler supporting the target processor. Furthermore, the specialized instruction set of the target processor is described in a parameterized way using a target processor-independent architecture description approach, thus allowing the support of any processor. The compiler has been used for the generation of application code for two different ASIPs for several benchmarks. The code generated by the compiler achieves a speedup between 2× --74× and 2× --97× compared to the code generated by the MathWorks MATLAB-to-C compiler. Experimental results also prove that the compiler efficiently exploits SIMD custom instructions achieving a 3.3 factor speedup compared to cases where no SIMD processing is used. Thus the compiler can be employed to reduce the development time/effort/cost and time to market through raising the abstraction of application design in an embedded systems/system-on-chip development context.

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Cited By

Macwan RBenezeth YMansouri A(2021)Generalized Eigenvalue Decomposition Applied to Estimation of Spatial rPPG Distribution of SkinJournal of Mathematical Imaging and Vision10.1007/s10851-021-01025-363:7(807-820)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s10851-021-01025-3
Latifis IParashar KDimitroulakos GCappelle HLezos CMasselos KCatthoor F(2020)A Retargetable MATLAB-to-C Compiler Exploiting Custom Instructions and Data ParallelismACM Transactions on Embedded Computing Systems10.1145/339189819:6(1-27)Online publication date: 3-Oct-2020
https://dl.acm.org/doi/10.1145/3391898

Index Terms

A MATLAB Vectorizing Compiler Targeting Application-Specific Instruction Set Processors
1. Hardware
  1. Very large scale integration design
    1. Application-specific VLSI designs
      1. Application specific instruction set processors
2. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Retargetable compilers
      2. Source code generation

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Published In

cover image ACM Transactions on Design Automation of Electronic Systems

ACM Transactions on Design Automation of Electronic Systems Volume 22, Issue 2

Special Section of IDEA: Integrating Dataflow, Embedded Computing, and Architecture

April 2017

458 pages

ISSN:1084-4309

EISSN:1557-7309

DOI:10.1145/3029795

Editor:
Naehyuck Chang
Korea Advanced Institute of Science and Technology, Korea

Issue’s Table of Contents

Copyright © 2017 ACM.

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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Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 04 January 2017

Accepted: 01 September 2016

Revised: 01 July 2016

Received: 01 February 2016

Published in TODAES Volume 22, Issue 2

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Cited By

Macwan RBenezeth YMansouri A(2021)Generalized Eigenvalue Decomposition Applied to Estimation of Spatial rPPG Distribution of SkinJournal of Mathematical Imaging and Vision10.1007/s10851-021-01025-363:7(807-820)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s10851-021-01025-3
Latifis IParashar KDimitroulakos GCappelle HLezos CMasselos KCatthoor F(2020)A Retargetable MATLAB-to-C Compiler Exploiting Custom Instructions and Data ParallelismACM Transactions on Embedded Computing Systems10.1145/339189819:6(1-27)Online publication date: 3-Oct-2020
https://dl.acm.org/doi/10.1145/3391898

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