Output details
11 - Computer Science and Informatics
University of St Andrews
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Output 0 of 0 in the submission
Output title
Reducing Training Time in a One-shot Machine Learning-based Compiler
Type
E - Conference contribution
Name of conference/published proceedings
Languages and Compilers for Parallel Computing : 22nd International Workshop, LCPC 2009, Newark, DE, USA, October 8-10, 2009, Revised Selected Papers
Volume number
5898
Issue number
-
First page of article
399
ISSN of proceedings
0302-9743
Year of publication
2010
URL
-
Number of additional authors
3
Additional information
<08>First paper to present a fully operational 'drop-in' replacement machine learning compiler, which does not rely on multiple compilations and search at compile time - transparently usable without profiling. Shows 14% speedup over a mature compiler (GCC-O3) on an industry standard benchmark suite (EEMBC). First use of unsupervised learning for compiler optimisation - allows the training of models to scale with a growing number of programs. Training time required for equivalent performance reduced by a factor of 7. The venue is technically a workshop, but has an important history, and is more highly regarded than many conferences in the area.
Interdisciplinary
-
Cross-referral requested
-
Research group
E - Programming languages
Citation count
2
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
