Difference between revisions of "Publications/verna.06.ijcs"
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| volume = 32 |
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| abstract = Contrary to popular belief, Lisp code can be very efficient today: it can run as fast as equivalent C code or even faster in some cases. In this paper, we explain how to tune Lisp code for performance by introducing the proper type declarations, using the appropriate data structures and compiler information. We also explain how efficiency is achieved by the compilers. These techniques are applied to simple image processing algorithms in order to demonstrate the announced performance on pixel access and arithmetic operations in both languages. |
| abstract = Contrary to popular belief, Lisp code can be very efficient today: it can run as fast as equivalent C code or even faster in some cases. In this paper, we explain how to tune Lisp code for performance by introducing the proper type declarations, using the appropriate data structures and compiler information. We also explain how efficiency is achieved by the compilers. These techniques are applied to simple image processing algorithms in order to demonstrate the announced performance on pixel access and arithmetic operations in both languages. |
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| type = article |
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month = dec, |
month = dec, |
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issn = <nowiki>{</nowiki>1819-656X<nowiki>}</nowiki>, |
issn = <nowiki>{</nowiki>1819-656X<nowiki>}</nowiki>, |
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− | project = <nowiki>{</nowiki>Software<nowiki>}</nowiki>, |
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abstract = <nowiki>{</nowiki>Contrary to popular belief, Lisp code can be very |
abstract = <nowiki>{</nowiki>Contrary to popular belief, Lisp code can be very |
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efficient today: it can run as fast as equivalent C code or |
efficient today: it can run as fast as equivalent C code or |
Revision as of 12:15, 26 April 2016
- Authors
- Didier Verna
- Journal
- IAENG International Journal of Computer Science
- Type
- article
- Projects
- Software"Software" is not in the list (Vaucanson, Spot, URBI, Olena, APMC, Tiger, Climb, Speaker ID, Transformers, Bison, ...) of allowed values for the "Related project" property.
- Date
- 2006-12-01
Abstract
Contrary to popular belief, Lisp code can be very efficient today: it can run as fast as equivalent C code or even faster in some cases. In this paper, we explain how to tune Lisp code for performance by introducing the proper type declarations, using the appropriate data structures and compiler information. We also explain how efficiency is achieved by the compilers. These techniques are applied to simple image processing algorithms in order to demonstrate the announced performance on pixel access and arithmetic operations in both languages.
Bibtex (lrde.bib)
@Article{ verna.06.ijcs, author = {Didier Verna}, title = {How to make Lisp go faster than {C}}, journal = {IAENG International Journal of Computer Science}, year = 2006, volume = 32, number = 4, month = dec, issn = {1819-656X}, abstract = {Contrary to popular belief, Lisp code can be very efficient today: it can run as fast as equivalent C code or even faster in some cases. In this paper, we explain how to tune Lisp code for performance by introducing the proper type declarations, using the appropriate data structures and compiler information. We also explain how efficiency is achieved by the compilers. These techniques are applied to simple image processing algorithms in order to demonstrate the announced performance on pixel access and arithmetic operations in both languages.} }