{"id":268593,"date":"2013-02-01T00:00:20","date_gmt":"2013-02-01T08:00:20","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=268593"},"modified":"2024-02-05T19:46:18","modified_gmt":"2024-02-06T03:46:18","slug":"relational-verification-simd-loop-synthesis","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/relational-verification-simd-loop-synthesis\/","title":{"rendered":"From Relational Verification to SIMD Loop Synthesis"},"content":{"rendered":"

Existing pattern-based compiler technology is unable to effectively exploit the full potential of SIMD architectures. We present a new program synthesis based technique for auto-vectorizing performance critical innermost loops. Our synthesis technique is applicable to a wide range of loops, consistently produces performant SIMD code, and generates correctness proofs for the output code. The synthesis technique, which leverages existing work on relational verification methods, is a novel combination of deductive loop restructuring, synthesis condition generation and a new inductive synthesis algorithm for producing loop-free code fragments. The inductive synthesis algorithm wraps an optimized depth-first exploration of code sequences inside a CEGIS loop. Our technique is able to quickly produce SIMD implementations (up to 9 instructions in 0.12 seconds) for a wide range of fundamental looping structures. The resulting SIMD implementations outperform the original loops by 2x-3x.<\/p>\n","protected":false},"excerpt":{"rendered":"

Existing pattern-based compiler technology is unable to effectively exploit the full potential of SIMD architectures. We present a new program synthesis based technique for auto-vectorizing performance critical innermost loops. Our synthesis technique is applicable to a wide range of loops, consistently produces performant SIMD code, and generates correctness proofs for the output code. The synthesis […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[246574],"research-area":[13560],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-268593","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-highlight-award","msr-research-area-programming-languages-software-engineering","msr-locale-en_us"],"msr_publishername":"Association for Computing 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