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Errors Classificati...
Errors Classification and Static Detection Techniques for Dual-Programming Model (OpenMP and OpenACC)
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- Basloom, Huda Saleh (author)
- King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Comp Sci, Jeddah 21514, Saudi Arabia.
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- Dahab, Mohamed Yehia (author)
- King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Comp Sci, Jeddah 21514, Saudi Arabia.;Agr Res Ctr ARC, Giza 12619, Egypt.
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- Alghamdi, Ahmed Mohammed (author)
- Univ Jeddah, Coll Comp Sci & Engn, Dept Software Engn, Jeddah 21493, Saudi Arabia.
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- Eassa, Fathy Elbouraey (author)
- King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Comp Sci, Jeddah 21514, Saudi Arabia.
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- Al-Ghamdi, Abdullah Saad Al-Malaise (author)
- King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Informat Syst, Jeddah 21589, Saudi Arabia.
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- Haridi, Seif, 1953- (author)
- KTH,Programvaruteknik och datorsystem, SCS
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King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Comp Sci, Jeddah 21514, Saudi Arabia King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Comp Sci, Jeddah 21514, Saudi Arabia.;Agr Res Ctr ARC, Giza 12619, Egypt. (creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2022
- 2022
- English.
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In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 117808-117826
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https://doi.org/10.1...
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Abstract
Subject headings
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- Recently, incorporating more than one programming model into a system designed for high performance computing (HPC) has become a popular solution to implementing parallel systems. Since traditional programming languages, such as C, C++, and Fortran, do not support parallelism at the level of multi-core processors and accelerators, many programmers add one or more programming models to achieve parallelism and accelerate computation efficiently. These models include Open Accelerators (OpenACC) and Open Multi-Processing (OpenMP), which have recently been used with various models, including Message Passing Interface (MPI) and Compute Unified Device Architecture (CUDA). Due to the difficulty of predicting the behavior of threads, runtime errors cannot be predicted. The compiler cannot identify runtime errors such as data races, race conditions, deadlocks, or livelocks. Many studies have been conducted on the development of testing tools to detect runtime errors when using programming models, such as the combinations of OpenACC with MPI models and OpenMP with MPI. Although more applications use OpenACC and OpenMP together, no testing tools have been developed to test these applications to date. This paper presents a testing tool for detecting runtime using a static testing technique. This tool can detect actual and potential runtime errors during the integration of the OpenACC and OpenMP models into systems developed in C++. This tool implement error dependency graphs, which are proposed in this paper. Additionally, a dependency graph of the errors is provided, along with a classification of runtime errors that result from combining the two programming models mentioned earlier.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Keyword
- Parallel programming
- high-performance computing
- OpenMP
- OpenACC
- deadlock
- runtime errors
- race condition
- static testing
- software testing
- testing tools classifications
- exascale systems
- programming models
Publication and Content Type
- ref (subject category)
- art (subject category)
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