Abstract
This paper proposes a new approach to improve data-parallel languages in the context of sparse and irregular computation. We analyze the capabilities of High Performance Fortran (HPF) and Vienna Fortran, and identify a set of problems leading to sub-optimal parallel code generation for such computations on distributed-memory machines. Finally, we propose extensions to the data distribution facilities in Vienna Fortran which address these issues and provide a powerful mechanism for efficiently expressing sparse algorithms.
This work was supported by the Ministry of Education and Science (CICYT) of Spain under project TIC92-0942 and by the Austrian Science Foundation(FWF).
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Ujaldon, M., Zapata, E.L., Chapman, B.M., Zima, H.P. (1996). Data-parallel Language Features for Sparse Codes. In: Szymanski, B.K., Sinharoy, B. (eds) Languages, Compilers and Run-Time Systems for Scalable Computers. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2315-4_19
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DOI: https://doi.org/10.1007/978-1-4615-2315-4_19
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