Flexible Control of Data Transfers between Parallel Programs

2005 ◽  
Author(s):  
J.S.-C. Wu ◽  
A. Sussman
Keyword(s):  
Parallel Programs ◽  
Flexible Control ◽  
Data Transfers

Generating data transfers for distributed GPU parallel programs

2013 ◽  
Vol 73 (12) ◽  
pp. 1649-1660 ◽  
Author(s):  
F. Silber-Chaussumier ◽  
A. Muller ◽  
R. Habel
Keyword(s):  
Parallel Programs ◽  
Data Transfers

scholarly journals Disentanglement in nested-parallel programs

2020 ◽  
Vol 4 (POPL) ◽  
pp. 1-32 ◽  
Author(s):  
Sam Westrick ◽  
Rohan Yadav ◽  
Matthew Fluet ◽  
Umut A. Acar
Keyword(s):  
Parallel Programs

Test-driven repair of data races in structured parallel programs

2014 ◽  
Vol 49 (6) ◽  
pp. 15-25 ◽  
Author(s):  
Rishi Surendran ◽  
Raghavan Raman ◽  
Swarat Chaudhuri ◽  
John Mellor-Crummey ◽  
Vivek Sarkar
Keyword(s):  
Parallel Programs ◽  
Data Races

scholarly journals Correct program parallelisations

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.

Sign in / Sign up

Export Citation Format

Share Document