Parallel language constructs for tensor product computations on loosely coupled architectures

Distributed memory architectures offer high levels of performance and flexibility, but have proven awkward to program. Current languages for nonshared memory architectures provide a relatively low-level programming environment, and are poorly suited to modular programming, and to the construction of...

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Veröffentlicht in:Proceedings of the 1989 ACM/IEEE conference on Supercomputing S. 616 - 626
Hauptverfasser: Mehrotra, P., van Rosendale, J.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: New York, NY, USA ACM 01.08.1989
IEEE
Schriftenreihe:ACM Conferences
Schlagworte:
Algorithm design and analysis
Computer architecture
Computer systems organization > Architectures > Parallel architectures
Computer systems organization > Architectures > Parallel architectures > Systolic arrays
Computing methodologies > Concurrent computing methodologies > Concurrent programming languages
Concurrent computing
Libraries
Memory architecture
Modular construction
Parallel languages
Parallel programming
Programming environments
Software and its engineering > Software notations and tools > General programming languages > Language features > Concurrent programming structures
Software and its engineering > Software notations and tools > General programming languages > Language types > Concurrent programming languages
Software and its engineering > Software organization and properties > Contextual software domains > Operating systems > Memory management > Distributed memory
Tensile stress
ISBN:9780897913416, 0897913418
Online-Zugang:Volltext
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Zusammenfassung:Distributed memory architectures offer high levels of performance and flexibility, but have proven awkward to program. Current languages for nonshared memory architectures provide a relatively low-level programming environment, and are poorly suited to modular programming, and to the construction of libraries. This paper describes a set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level. We focus here on tensor product array computations, a simple but important class of numerical algorithms. We consider first the problem of programming one dimensional "kernel" routines, such as parallel tridiagonal solvers, and after that look at how such parallel kernels can be combined to form parallel tensor product algorithms.
Bibliographie:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780897913416
0897913418
DOI:10.1145/76263.76333