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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  1/2018 - 4

An Automatic Instruction-Level Parallelization of Machine Code

MARINKOVIC, V. See more information about MARINKOVIC, V. on SCOPUS See more information about MARINKOVIC, V. on IEEExplore See more information about MARINKOVIC, V. on Web of Science, POPOVIC, M. See more information about  POPOVIC, M. on SCOPUS See more information about  POPOVIC, M. on SCOPUS See more information about POPOVIC, M. on Web of Science, DJUKIC, M. See more information about DJUKIC, M. on SCOPUS See more information about DJUKIC, M. on SCOPUS See more information about DJUKIC, M. on Web of Science
 
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Download PDF pdficon (1,217 KB) | Citation | Downloads: 960 | Views: 2,754

Author keywords
parallel architectures, parallel programming, multicore processing, assembly, processor scheduling

References keywords
parallel(13), code(10), parallelization(9), automatic(8), systems(7), programming(4), program(4), micro(4), data(4), architectures(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 27 - 36
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01004
Web of Science Accession Number: 000426449500004
SCOPUS ID: 85043242372

Abstract
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Prevailing multicores and novel manycores have made a great challenge of modern day - parallelization of embedded software that is still written as sequential. In this paper, automatic code parallelization is considered, focusing on developing a parallelization tool at the binary level as well as on the validation of this approach. The novel instruction-level parallelization algorithm for assembly code which uses the register names after SSA to find independent blocks of code and then to schedule independent blocks using METIS to achieve good load balance is developed. The sequential consistency is verified and the validation is done by measuring the program execution time on the target architecture. Great speedup, taken as the performance measure in the validation process, and optimal load balancing are achieved for multicore RISC processors with 2 to 16 cores (e.g. MIPS, MicroBlaze, etc.). In particular, for 16 cores, the average speedup is 7.92x, while in some cases it reaches 14x. An approach to automatic parallelization provided by this paper is useful to researchers and developers in the area of parallelization as the basis for further optimizations, as the back-end of a compiler, or as the code parallelization tool for an embedded system.


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References Weight

Web of Science® Citations for all references: 3,511 TCR
SCOPUS® Citations for all references: 5,527 TCR

Web of Science® Average Citations per reference: 100 ACR
SCOPUS® Average Citations per reference: 158 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-11-17 18:58 in 208 seconds.




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