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Bio
He is a world leader in the field of high-performance domain-specific languages. Prof. Amarasinghe's group developed the Halide, TACO, Simit, StreamIt, StreamJIT, PetaBricks, MILK, Cimple, and GraphIt domain-specific languages and compilers, all of which combine language design and sophisticated compilation techniques to deliver unprecedented performance for targeted application domains such as image processing, stream computations, and graph analytics. Dr. Amarasinghe also pioneered the application of machine learning for compiler optimizations, from Meta optimization in 2003 to OpenTuner extendable autotuner today. With professor Anant Agarwal, he co-led the Raw architecture project, which did pioneering work on scalable multicores.
Research Interests
Papers共 289 篇Author StatisticsCo-AuthorSimilar Experts
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arxiv(2024)
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CoRR (2024): 647-670
arxiv(2024)
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CoRR (2024)
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2024 IEEE/ACM INTERNATIONAL SYMPOSIUM ON CODE GENERATION AND OPTIMIZATION, CGOpp.41-54, (2024)
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Lina Mezdour, Khadidja Kadem,Massinissa Merouani,Amina Selma Haichour,Saman Amarasinghe,Riyadh Baghdadi
PROCEEDINGS OF THE 32ND ACM SIGPLAN INTERNATIONAL CONFERENCE ON COMPILER CONSTRUCTION, CC 2023pp.50-60, (2023)
Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimizationpp.41-54, (2023)
ICLR 2023 (2023)
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ASPLOS (2)pp.920-934, (2023)
Conference on Machine Learning and Systems (2023)
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