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Timing neural networks in C and ada

Published: 04 November 2007 Publication History

Abstract

In this paper, we describe a neural network program that was originally developed in C, then ported to Ada 2005. We explain several simple modifications to the Ada code that reduce the overhead from 76% to 0%. These modifications could provide significant performance gains to other applications, allowing them to combine the safety of Ada with the speed of C. such a complicated data structure. In Section 3, we explain how we modified the code in translating it to Ada. Section 4 describes how we made simple changes to the Ada implementation to eliminate the additional overhead. Section 5 provides conclusions and insights for future projects.

References

[1]
Tennebo, Frode. (December, 2000). Elegance of Java and the Efficiency of C-It's Ada. Linux Journal. {Online}. Available: http://www.linuxjournal.com/article/4342.
[2]
Weiskirchner, Marcus. (September, 2003). Comparison of the Execution Times of Ada, C and Java. {Online}. Available: http://www.aicas.com/info/EADS_benchmark_language_comparison.pdf.
[3]
Corlan, A. D. "Language Benchmarks." {Online}. Available: http://dan.corlan.net/bench.html.
[4]
Kuhn, Markus. "Markus Kuhn's Ada95 page." {Online}. Available: http://www.cl.cam.ac.uk/~mgk25/ada.html.

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Published In

cover image ACM SIGAda Ada Letters
ACM SIGAda Ada Letters  Volume XXVII, Issue 3
SIGAda '07
December 2007
93 pages
ISSN:1094-3641
DOI:10.1145/1315607
Issue’s Table of Contents
  • cover image ACM Conferences
    SIGAda '07: Proceedings of the 2007 ACM international conference on SIGAda annual international conference
    November 2007
    116 pages
    ISBN:9781595938763
    DOI:10.1145/1315580
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

Publication History

Published: 04 November 2007
Published in SIGADA Volume XXVII, Issue 3

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Author Tags

  1. C
  2. ada
  3. benchmarking
  4. neural networks

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