From transformations to methodology in parallel program development: A case study
The Bird-Meertens formalism (BMF) of higher-order functions over lists is a mathematical framework supporting formal derivation of algorithms from functional specifications. This paper reports results of a case study on the systematic use of BMF in the process of parallel program development. We dev...
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| Published in | Microprocessing and microprogramming Vol. 41; no. 8; pp. 571 - 588 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.04.1996
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0165-6074 |
| DOI | 10.1016/0165-6074(96)00004-X |
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| Abstract | The Bird-Meertens formalism (BMF) of higher-order functions over lists is a mathematical framework supporting formal derivation of algorithms from functional specifications. This paper reports results of a case study on the systematic use of BMF in the process of parallel program development. We develop a parallel program for polynomial multiplication, starting with a straight-forward mathematical specification and arriving at the target processor topology together with a program for each processor of it. The development process is based on formal transformations; design decisions concerning data partitioning, processor interconnections, etc. are governed by formal type analysis and performance estimation rather than made
ad hoc. The parallel target implementation is parameterized for an arbitrary number of processors; for the particular number, the target program is both time and cost-optimal. We compare our results with systolic solutions to polynomial multiplication. |
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| AbstractList | The Bird-Meertens formalism (BMF) of higher-order functions over lists is a mathematical framework supporting formal derivation of algorithms from functional specifications. This paper reports results of a case study on the systematic use of BMF in the process of parallel program development. We develop a parallel program for polynomial multiplication, starting with a straight-forward mathematical specification and arriving at the target processor topology together with a program for each processor of it. The development process is based on formal transformations; design decisions concerning data partitioning, processor interconnections, etc. are governed by formal type analysis and performance estimation rather than made ad hoc. The parallel target implementation is parameterized for an arbitrary number of processors; for the particular number, the target program is both time and cost-optimal. We compare our results with systolic solutions to polynomial multiplication. The Bird-Meertens formalism (BMF) of higher-order functions over lists is a mathematical framework supporting formal derivation of algorithms from functional specifications. This paper reports results of a case study on the systematic use of BMF in the process of parallel program development. We develop a parallel program for polynomial multiplication, starting with a straight-forward mathematical specification and arriving at the target processor topology together with a program for each processor of it. The development process is based on formal transformations; design decisions concerning data partitioning, processor interconnections, etc. are governed by formal type analysis and performance estimation rather than made ad hoc. The parallel target implementation is parameterized for an arbitrary number of processors; for the particular number, the target program is both time and cost-optimal. We compare our results with systolic solutions to polynomial multiplication. |
| Author | Gorlatch, Sergei |
| Author_xml | – sequence: 1 givenname: Sergei surname: Gorlatch fullname: Gorlatch, Sergei email: gorlatch@fmi.uni-passau.de organization: Universität Passau, D-94030 Passau, Germany |
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| Keywords | Bird-Meertens formalism Formal specification and design Parallelization Program transformation |
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Ruby – start-page: 398 year: 1993 ident: 10.1016/0165-6074(96)00004-X_BIB20 article-title: Loop parallelization in the polytope model |
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