Name
Abstract | ||
|---|---|---|
The authors present an algebraic theory, based on the tensor product for describing the semantics of regular data distributions such as block, cyclic, and block-cyclic distributions. These distributions have been proposed in high performance Fortran, an ongoing effort for developing a Fortran extension for massively parallel computing. This algebraic theory has been used for designing and implementing block recursive algorithms on shared-memory and vector multiprocessors. In the present work, the authors extend this theory to generate programs with explicit data distribution commands from tensor product formulas. A methodology to generate data distributions that optimize communication is described. This methodology is demonstrated by generating efficient programs with data distribution for the fast Fourier transform. |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1109/SPDP.1992.242712 | SPDP |
Keywords | Field | DocType |
block,distributed memory,shared memory,recursive algorithm,algorithm design and analysis,massively parallel computing,cyclic,distributed computing,semantics,computer science,fast fourier transforms,tensile stress,fast fourier transform,generic programming,nist,tensor product | Tensor product,Algorithm design,Computer science,Massively parallel,Parallel computing,Fortran,Fast Fourier transform,Algebraic theory,High Performance Fortran,Recursion,Distributed computing | Conference |
ISBN | Citations | PageRank |
0-8186-3200-3 | 9 | 2.16 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandeep K. S. Gupta | 1 | 2572 | 219.25 |
| S. D. Kaushik | 2 | 291 | 25.26 |
| Chua-huang Huang | 3 | 281 | 35.34 |
| John R. Johnson | 4 | 34 | 7.30 |
| Rodney W. Johnson | 5 | 534 | 294.39 |
| P. Sadayappan | 6 | 4821 | 344.32 |