Name
Abstract | ||
|---|---|---|
As one of the popularparallel programming interfaces, OpenMP has been widely used in many scientific applications in order to facilitate shared-memory parallelism. With the increasing popularity of multi-core machines, more and more sequential programs are being parallelized using OpenMP. However, it is not easy for programmers to write parallel programs correctly. Concurrency errors, such as data races and deadlocks. This paper presents a novel technique to detect data races and deadlocks using hybrid program analysis. Previous work [2] has shown the symbolic execution on GPU program, our tool exploits SMT solver to detect errors in OpenMP program. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICPPW.2012.83 | ICPP Workshops |
Keywords | Field | DocType |
shared-memory parallelism,parallel program,data races detection,application program interfaces,gpu program,parallel programming interfaces,novel technique,symbolic execution,parallel programming,openmp analyzer,concurrency error,graphics processing units,hybrid program analysis,data race,multi-core machine,increasing popularity,shared memory systems,deadlocks detection,smt solver,program diagnostics,multicore machines,detecting concurrency errors,concurrency error detection,openmp,sequential programs,sequential program,concurrent computing,benchmark testing | Programming language,Concurrency,Computer science,System recovery,Deadlock,Parallel computing,Program analysis,Concurrent computing,Spectrum analyzer,Benchmark (computing),Distributed computing,Satisfiability modulo theories | Conference |
ISSN | ISBN | Citations |
1530-2016 | 978-1-4673-2509-7 | 1 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongyi Ma | 1 | 32 | 2.37 |
| Qichang Chen | 2 | 73 | 5.34 |
| Liqiang Wang | 3 | 703 | 56.71 |
| Chunhua Liao | 4 | 330 | 30.72 |
| Daniel Quinlan | 5 | 139 | 8.27 |