Efficient incremental run-time specialization for free Export

@inproceedings{citeulike:104213, abstract = {Availability of data in a program determines computation stages. Incremental partial evaluation exploit these stages for optimization: it allows further specialization to be performed as data become available at later stages. The fundamental advantage of incremental specialization is to factorize the specialization process. As a result, specializing a program at a given stage costs considerably less than specializing it once all the data are available.We present a realistic and flexible approach to achieve efficient incremental run-time specialization. Rather than developing specific techniques, as previously proposed, we are able to re-use existing technology by iterating a specialization process. Moreover, in doing so, we do not lose any specialization opportunities. This approach makes it possible to exploit nested quasi-invariants and to speed up the run-time specialization process.This approach has been implemented in Tempo, a specializer for C programs that is publicly available. A preliminary experiment confirm that incremental that incremental specialization can greatly speed up the specialization process.}, address = {New York, NY, USA}, author = {Marlet, Renaud and Consel, Charles and Boinot, Philippe}, booktitle = {PLDI '99: Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation}, citeulike-article-id = {104213}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=301618.301681}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/301618.301681}, doi = {10.1145/301618.301681}, isbn = {1-58113-094-5}, issn = {0362-1340}, keywords = {on-line, partial-evaluation}, location = {Atlanta, Georgia, United States}, month = {May}, number = {5}, pages = {281--292}, posted-at = {2006-03-30 10:36:04}, priority = {2}, publisher = {ACM}, title = {Efficient incremental run-time specialization for free}, url = {http://dx.doi.org/10.1145/301618.301681}, volume = {34}, year = {1999} }

TY - CONF ID - citeulike:104213 L3 - citeulike-article-id:104213 N2 - Availability of data in a program determines computation stages. Incremental partial evaluation exploit these stages for optimization: it allows further specialization to be performed as data become available at later stages. The fundamental advantage of incremental specialization is to factorize the specialization process. As a result, specializing a program at a given stage costs considerably less than specializing it once all the data are available.We present a realistic and flexible approach to achieve efficient incremental run-time specialization. Rather than developing specific techniques, as previously proposed, we are able to re-use existing technology by iterating a specialization process. Moreover, in doing so, we do not lose any specialization opportunities. This approach makes it possible to exploit nested quasi-invariants and to speed up the run-time specialization process.This approach has been implemented in Tempo, a specializer for C programs that is publicly available. A preliminary experiment confirm that incremental that incremental specialization can greatly speed up the specialization process. CY - Atlanta, Georgia, United States IS - 5 SN - 1-58113-094-5 AD - New York, NY, USA EP - 292 TI - Efficient incremental run-time specialization for free PB - ACM VL - 34 T2 - PLDI '99: Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation SP - 281 KW - on-line KW - partial-evaluation AU - Marlet, Renaud AU - Consel, Charles AU - Boinot, Philippe PY - 1999/05// UR - http://dx.doi.org/10.1145/301618.301681 ER -