An application-level dependable technique for farmer-worker parallel programs

An algorithm for all-du-path testing coverage of shared memory parallel programs

Proceedings Sixth Asian Test Symposium (ATS'97) ◽

10.1109/ats.1997.643968 ◽

2002 ◽

Cited By ~ 1

Author(s):

C.-S.D. Yang ◽

L.L. Pollock

Keyword(s):

Shared Memory ◽

Parallel Programs ◽

Path Testing ◽

Testing Coverage

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Disentanglement in nested-parallel programs

Proceedings of the ACM on Programming Languages ◽

10.1145/3371115 ◽

2020 ◽

Vol 4 (POPL) ◽

pp. 1-32 ◽

Cited By ~ 2

Author(s):

Sam Westrick ◽

Rohan Yadav ◽

Matthew Fluet ◽

Umut A. Acar

Keyword(s):

Parallel Programs

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Test-driven repair of data races in structured parallel programs

ACM SIGPLAN Notices ◽

10.1145/2666356.2594335 ◽

2014 ◽

Vol 49 (6) ◽

pp. 15-25 ◽

Cited By ~ 3

Author(s):

Rishi Surendran ◽

Raghavan Raman ◽

Swarat Chaudhuri ◽

John Mellor-Crummey ◽

Vivek Sarkar

Keyword(s):

Parallel Programs ◽

Data Races

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Monit: a performance monitoring tool for parallel and pseudo-parallel programs

ACM SIGMETRICS Performance Evaluation Review ◽

10.1145/29904.29923 ◽

1987 ◽

Vol 15 (1) ◽

pp. 163-174 ◽

Cited By ~ 2

Author(s):

Teemu Kerola ◽

Herb Schwetman

Keyword(s):

Performance Monitoring ◽

Parallel Programs ◽

Monitoring Tool ◽

A Performance

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Correct program parallelisations

International Journal on Software Tools for Technology Transfer ◽

10.1007/s10009-020-00601-z ◽

2021 ◽

Author(s):

S. Blom ◽

S. Darabi ◽

M. Huisman ◽

M. Safari

Keyword(s):

Composition Operators ◽

Parallel Programs ◽

Parallel Program ◽

Tool Support ◽

Intermediate Representation ◽

Data Race ◽

Sequential Program ◽

Functional Correctness ◽

Correct Program ◽

Basic Blocks

AbstractA commonly used approach to develop deterministic parallel programs is to augment a sequential program with compiler directives that indicate which program blocks may potentially be executed in parallel. This paper develops a verification technique to reason about such compiler directives, in particular to show that they do not change the behaviour of the program. Moreover, the verification technique is tool-supported and can be combined with proving functional correctness of the program. To develop our verification technique, we propose a simple intermediate representation (syntax and semantics) that captures the main forms of deterministic parallel programs. This language distinguishes three kinds of basic blocks: parallel, vectorised and sequential blocks, which can be composed using three different composition operators: sequential, parallel and fusion composition. We show how a widely used subset of OpenMP can be encoded into this intermediate representation. Our verification technique builds on the notion of iteration contract to specify the behaviour of basic blocks; we show that if iteration contracts are manually specified for single blocks, then that is sufficient to automatically reason about data race freedom of the composed program. Moreover, we also show that it is sufficient to establish functional correctness on a linearised version of the original program to conclude functional correctness of the parallel program. Finally, we exemplify our approach on an example OpenMP program, and we discuss how tool support is provided.

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