{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T05:40:33Z","timestamp":1694497233319},"reference-count":10,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2008,6,6]],"date-time":"2008-06-06T00:00:00Z","timestamp":1212710400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2009,1]]},"abstract":"Abstract<\/jats:title>An optimizing compiler cannot generate one best code pattern for all input data. There is no \u2018one optimization fits all\u2019 inputs. To attain high performance for a large range of inputs, it is therefore desirable to resort to some kind of specialization. Data specialization significantly improves the performance delivered by the compiler\u2010generated codes. Specialization is, however, limited by code expansion and introduces a time overhead for the selection of the appropriate version. We propose a new method to specialize the code at the assembly level for loop structures. Our specialization scheme focuses on different ranges of loop trip count and combines all these versions into a code that switches smoothly from one to the other while the iteration count increases. Hence, the resulting code achieves the same level of performance than each version on its specific iteration interval. We illustrate the benefit of our method on the SPEC benchmarks with detailed experimental results. 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