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dc.contributor.authorJangda, Aen_US
dc.contributor.authorYORSH, Gen_US
dc.contributor.authorOnward! 2017 Proceedings of the 2017 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Softwareen_US
dc.date.accessioned2017-12-07T14:45:39Z
dc.date.available2017-07-28en_US
dc.date.issued2017-10-25en_US
dc.date.submitted2017-11-29T13:57:22.558Z
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/29154
dc.description.abstractOur aim is to enable software to take full advantage of the capabilities of emerging microprocessor designs without modifying the compiler. Towards this end, we propose a new approach to code generation and optimization. Our approach uses an SMT solver in a novel way to generate efficient code for modern architectures and guarantee that the generated code correctly implements the source code. The distinguishing characteristic of our approach is that the size of the constraints does not depend on the candidate sequence of instructions. To study the feasibility of our approach, we implemented a preliminary prototype, which takes as input LLVM IR code and uses Z3 SMT solver to generate ARMv7-A assembly. The prototype handles arbitrary loop-free code (not only basic blocks) as input and output. We applied it to small but tricky examples used as standard benchmarks for other superoptimization and synthesis tools. We are encouraged to see that Z3 successfully solved complex constraints that arise from our approach. This work paves the way to employing recent advances in SMT solvers and has a potential to advance SMT solvers further by providing a new category of challenging benchmarks that come from an industrial application domain.en_US
dc.rightsThis is a pre-copyedited, author-produced version of an article accepted for publication in Proceedings of the 2017 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software following peer review. The version of record is available https://dl.acm.org/citation.cfm?doid=3133850.3133856
dc.titleUnbounded Superoptimizationen_US
dc.typeConference Proceeding
dc.rights.holderCopyright © 2017 ACM, Inc.
dc.identifier.doi10.1145/3133850.3133856en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
dcterms.dateAccepted2017-07-28en_US


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