The authors document the performance of these compilers on a variety of benchmark programs and present several case studies.
Hardback
Publication Date: 21/02/1992
MIMD computers are considered difficult to program. "Data-Parallel Programming" demonstrates that architecture-independent parallel programming is possible by describing in detail how programs written in a high-level SIMD programming language may be compiled and efficiently executed on both shared-memory multiprocessors and distributed-memory multicomputers. The authors provide enough data so that the reader can decide the feasibility of architecture-independent programming in a data-parallel language. For each benchmark program they give the source code listing, absolute execution time on both a multiprocessor and a multicomputer, and a speed-up relative to a sequential program. And they often present multiple solutions to the same problem, to better illustrate the strengths and weaknesses of these compilers. The language presented is Dataparallel C, a variant of the original C* language developed by Thinking Machines Corporation for its Connection Machine processor array. Separate chapters describe the compilation of Dataparallel C programs for execution on the Sequent mulitprocessor and the Intel and nCUBE hypercubes, respectively.
The authors document the performance of these compilers on a variety of benchmark programs and present several case studies.
The authors document the performance of these compilers on a variety of benchmark programs and present several case studies.
- ISBN:
- 9780262082051
- 9780262082051
- Category:
- Computer architecture & logic design
- Format:
- Hardback
- Publication Date:
- 21-02-1992
- Language:
- English
- Publisher:
- MIT Press Ltd
- Country of origin:
- United States
- Pages:
- 250
- Dimensions (mm):
- 231x180x20mm
- Weight:
- 0.61kg
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