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CROPS: coordinated restructuring of programs and storage
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Data Relation Vectors: A New Abstraction for Data Optimizations
IEEE Transactions on Computers - Special issue on the parallel architecture and compilation techniques conference
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Rescheduling for Locality in Sparse Matrix Computations
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PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Array Regrouping and Its Use in Compiling Data-Intensive Embedded Applications
IEEE Transactions on Computers
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IEEE Transactions on Parallel and Distributed Systems
Runtime characterisation of irregular accesses applied to parallelisation of irregular reductions
International Journal of Computational Science and Engineering
A comparison of programming models for multiprocessors with explicitly managed memory hierarchies
Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming
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LCPC'02 Proceedings of the 15th international conference on Languages and Compilers for Parallel Computing
Automatically enhancing locality for tree traversals with traversal splicing
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Non-affine Extensions to Polyhedral Code Generation
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Existing techniques can enhance the locality of arrays indexed by affine functions of induction variables. This paper presents a technique to localize non-affine array references, such as the indirect memory references common in sparse-matrix computations. Our optimization combines elements of tiling, data-centric tiling, data remapping and inspector-executor parallelization.We describe our technique, bucket tiling, which includes the tasks of permutation generation, data remapping, and loop regeneration. We show that profitability cannot generally be determined at compile-time, but requires an extension to run-time. We demonstrate our technique on three codes: integer sort, conjugate gradient, and a kernel used in simulating a beating heart. We observe speedups of 1.91 on integer sort, 1.57 on conjugate gradient, and 2.69 on the heart kernel.