| 000 | 03670nam a22005895i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-71489-9 | ||
| 003 | DE-He213 | ||
| 005 | 20220801221230.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 171222s2018 sz | s |||| 0|eng d | ||
| 020 |
_a9783319714899 _9978-3-319-71489-9 |
||
| 024 | 7 |
_a10.1007/978-3-319-71489-9 _2doi |
|
| 050 | 4 | _aQ342 | |
| 072 | 7 |
_aUYQ _2bicssc |
|
| 072 | 7 |
_aTEC009000 _2bisacsh |
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| 072 | 7 |
_aUYQ _2thema |
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| 082 | 0 | 4 |
_a006.3 _223 |
| 100 | 1 |
_aAshouri, Amir H. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _954832 |
|
| 245 | 1 | 0 |
_aAutomatic Tuning of Compilers Using Machine Learning _h[electronic resource] / _cby Amir H. Ashouri, Gianluca Palermo, John Cavazos, Cristina Silvano. |
| 250 | _a1st ed. 2018. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
|
| 300 |
_aXVII, 118 p. 23 illus., 6 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aPoliMI SpringerBriefs, _x2282-2585 |
|
| 505 | 0 | _aBackground -- DSE Approach for Compiler Passes -- Addressing the Selection Problem of Passes using ML -- Intermediate Speedup Prediction for the Phase-ordering Problem -- Full-sequence Speedup Prediction for the Phase-ordering Problem -- Concluding Remarks. . | |
| 520 | _aThis book explores break-through approaches to tackling and mitigating the well-known problems of compiler optimization using design space exploration and machine learning techniques. It demonstrates that not all the optimization passes are suitable for use within an optimization sequence and that, in fact, many of the available passes tend to counteract one another. After providing a comprehensive survey of currently available methodologies, including many experimental comparisons with state-of-the-art compiler frameworks, the book describes new approaches to solving the problem of selecting the best compiler optimizations and the phase-ordering problem, allowing readers to overcome the enormous complexity of choosing the right order of optimizations for each code segment in an application. As such, the book offers a valuable resource for a broad readership, including researchers interested in Computer Architecture, Electronic Design Automation and Machine Learning, as well as computer architects and compiler developers. | ||
| 650 | 0 |
_aComputational intelligence. _97716 |
|
| 650 | 0 |
_aCompilers (Computer programs). _93350 |
|
| 650 | 0 |
_aComputer simulation. _95106 |
|
| 650 | 0 |
_aArtificial intelligence. _93407 |
|
| 650 | 1 | 4 |
_aComputational Intelligence. _97716 |
| 650 | 2 | 4 |
_aCompilers and Interpreters. _931853 |
| 650 | 2 | 4 |
_aComputer Modelling. _954833 |
| 650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
| 700 | 1 |
_aPalermo, Gianluca. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _954834 |
|
| 700 | 1 |
_aCavazos, John. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _954835 |
|
| 700 | 1 |
_aSilvano, Cristina. _eauthor. _0(orcid)0000-0003-1668-0883 _1https://orcid.org/0000-0003-1668-0883 _4aut _4http://id.loc.gov/vocabulary/relators/aut _954836 |
|
| 710 | 2 |
_aSpringerLink (Online service) _954837 |
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| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319714882 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319714905 |
| 830 | 0 |
_aPoliMI SpringerBriefs, _x2282-2585 _954838 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-71489-9 |
| 912 | _aZDB-2-ENG | ||
| 912 | _aZDB-2-SXE | ||
| 942 | _cEBK | ||
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