Selected papers of the second workshop on Languages and compilers for parallel computing
A singular loop transformation framework based on non-singular matrices
International Journal of Parallel Programming
Symbolic analysis for parallelizing compilers
ACM Transactions on Programming Languages and Systems (TOPLAS)
Commutativity analysis: a new analysis technique for parallelizing compilers
ACM Transactions on Programming Languages and Systems (TOPLAS)
IEEE Transactions on Parallel and Distributed Systems
Synthesizing transformations for locality enhancement of imperfectly-nested loop nests
Proceedings of the 14th international conference on Supercomputing
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
ACM Transactions on Programming Languages and Systems (TOPLAS)
Prospectus for the next LAPACK and ScaLAPACK libraries
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Implementing linear algebra routines on multi-core processors with pipelining and a look ahead
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Mobile pipelines: parallelizing left-looking algorithms using navigational programming
HiPC'05 Proceedings of the 12th international conference on High Performance Computing
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Fractal symbolic analysis is a symbolic analysis technique for verifying the legality of program transformations. It is strictly more powerful than dependence analysis; for example, it can be used to verify the legality of blocking LU factorization with pivoting, a task for which dependence analysis is inadequate. In this paper, we show how fractal symbolic analysis can be used to convert between left- and right-looking versions of three kernels of central importance in computational science: triangular solve, Cholesky factorization, and LU factorization with pivoting.