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Using an architectural knowledge base to generate code for parallel computers

Authors:

A. E. Terrano,

S. M. Dunn,

J. E. PetersAuthors Info & Claims

CSC '89: Proceedings of the 17th conference on ACM Annual Computer Science Conference

Pages 239 - 244

https://doi.org/10.1145/75427.75457

Published: 21 February 1989 Publication History

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Abstract

Code generation for existing parallel computers involves partitioning the work into schedulable units, assigning the resulting computational units to specific processors, and generating the code for interprocessor communication and synchronization. The options for partitioning and mapping depend in detail on the problem being solved and the algorithm and architecture being used. For each new combination of problem, algorithm, and architecture, a new partitioning and mapping must be created and evaluated based on the actual communication costs incurred. If a particular choice of partition and map is found to be too inefficient when the communication cost is analyzed, it is usually necessary to repeat the code generation process from the beginning.

Given the complexity of this problem, it is not practical to develop a general algorithmic approach. A more promising approach is to develop restricted code generation strategies which are suitable for a class of problems and architectures, and compilers which use heuristic advice to guide code generation.

In this paper we present a compiler for distributed memory parallel computers which perform automatic program partitioning, mapping and communication code generation under the guidance of a strategy rule-base. All partitioning and mapping is performed automatically, and communication primitives are generated. We describe the compiler system and present an example code generation strategy for iterative elliptic partial differential equation solvers.

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Cited By

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Dunn SPeters JFinkel BNeafsey L(1990)DISIPLE: digital signal processor programming language and environmentIEEE Transactions on Acoustics, Speech, and Signal Processing10.1109/29.10310038:11(2001-2003)Online publication date: Jan-1990
https://doi.org/10.1109/29.103100
Peters JDunn S(1989)A compiler that easily retargets high level language programs for different signal processing architecturesInternational Conference on Acoustics, Speech, and Signal Processing10.1109/ICASSP.1989.266625(1103-1106)Online publication date: 1989
https://doi.org/10.1109/ICASSP.1989.266625

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Using an architectural knowledge base to generate code for parallel computers

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Published In

CSC '89: Proceedings of the 17th conference on ACM Annual Computer Science Conference

February 1989

121 pages

ISBN:0897912993

DOI:10.1145/75427

Conference Chair:
Arthur M. Riehl
University of Louisville

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 February 1989

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ICMI05

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ICMI05: Seventh International Conference on Multimodal Interfaces 2005

February 21 - 23, 1989

Kentucky, Louisville

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Dunn SPeters JFinkel BNeafsey L(1990)DISIPLE: digital signal processor programming language and environmentIEEE Transactions on Acoustics, Speech, and Signal Processing10.1109/29.10310038:11(2001-2003)Online publication date: Jan-1990
https://doi.org/10.1109/29.103100
Peters JDunn S(1989)A compiler that easily retargets high level language programs for different signal processing architecturesInternational Conference on Acoustics, Speech, and Signal Processing10.1109/ICASSP.1989.266625(1103-1106)Online publication date: 1989
https://doi.org/10.1109/ICASSP.1989.266625

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Using an architectural knowledge base to generate code for parallel computers

Are architectural smells independent from code smells? An empirical study

Using dynamic programming to generate optimized code in a Graham-Glanville style code generator