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dc.contributor.advisorChlipala, Adam
dc.contributor.advisorRagan-Kelley, Jonathan
dc.contributor.authorLiu, Amanda
dc.date.accessioned2022-08-29T16:07:12Z
dc.date.available2022-08-29T16:07:12Z
dc.date.issued2022-05
dc.date.submitted2022-06-21T19:25:47.865Z
dc.identifier.urihttps://hdl.handle.net/1721.1/144722
dc.description.abstractI propose a lightweight Coq framework for optimizing tensor kernels written in a pure, functional array language. Optimizations rely on user scheduling using series of verified, semantics-preserving rewrites. Unusually for compilation targeting imperative code with arrays and nested loops, all rewrites are source-to-source within a purely functional language. This language comprises a set of core constructs for expressing high-level computation detail and a set of what we call reshape operators, which can be derived from core constructs but trigger low-level decisions about storage patterns and ordering. We will demonstrate that not only is this system capable of deriving the optimizations of existing state-of-the-art languages like Halide and generating comparably performant code, it is also able to schedule a family of useful program transformations beyond what is reachable in Halide.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleVerified Scheduling Via High-Level Scheduling Rewrites
dc.typeThesis
dc.description.degreeS.M.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.orcidhttps://orcid.org/ 0000-0001-5549-9177
mit.thesis.degreeMaster
thesis.degree.nameMaster of Science in Electrical Engineering and Computer Science


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