ACC_TEST: Hybrid Testing Approach for OpenACC-Based Programs

Eassa, Fathy; Alghamdi, Ahmed Mohammed; Haridi, Seif; Khemakhem, Maher; AL-Ghamdi, Abdullah S. AL-Malaise; Alsolami, Eesa

doi:10.1109/access.2020.2991009

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…This integration may increase the time required to debug errors, but the intended advantage of identifying the largest number of potential and actual runtime errors will boost their use. Meany research used hybrid testing techniques such as: [30][31][32][33][34]. As a result, the type and behavior of runtime errors decide the procedures that should be employed.…”

Section: Related Workmentioning

confidence: 99%

“…The MPI programming model is well-known and essential because it distributes work among several devices in a distributed computing environment. OpenACC has been used in five of the thirteen programs that have been created to increase performance on the world's top supercomputers [1,33,34,48]. Furthermore, OpenACC is used by three of the top five high-performance computing applications.…”

Section: Hybrid Programming Modelsmentioning

confidence: 99%

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A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

Basloom¹,

Dahab²,

AL-Ghamdi³

et al. 2023

Computers, Materials &Amp; Continua

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Recently, researchers have shown increasing interest in combining more than one programming model into systems running on high performance computing systems (HPCs) to achieve exascale by applying parallelism at multiple levels. Combining different programming paradigms, such as Message Passing Interface (MPI), Open Multiple Processing (OpenMP), and Open Accelerators (OpenACC), can increase computation speed and improve performance. During the integration of multiple models, the probability of runtime errors increases, making their detection difficult, especially in the absence of testing techniques that can detect these errors. Numerous studies have been conducted to identify these errors, but no technique exists for detecting errors in three-level programming models. Despite the increasing research that integrates the three programming models, MPI, OpenMP, and OpenACC, a testing technology to detect runtime errors, such as deadlocks and race conditions, which can arise from this integration has not been developed. Therefore, this paper begins with a definition and explanation of runtime errors that result from integrating the three programming models that compilers cannot detect. For the first time, this paper presents a classification of operational errors that can result from the integration of the three models. This paper also proposes a parallel hybrid testing technique for detecting runtime errors in systems built in the C++ programming language that uses the triple programming models MPI, OpenMP, and OpenACC. This hybrid technology combines static technology and dynamic technology, given that some errors can be detected using static techniques, whereas others can be detected using dynamic technology. The hybrid technique can detect more errors because it combines two distinct technologies. The proposed static technology detects a wide range of error types in less time, whereas a portion of the potential errors that may or may not occur depending on the 4502 CMC, 2023, vol.74, no.2 operating environment are left to the dynamic technology, which completes the validation.

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Section: Related Workmentioning

confidence: 99%

Section: Hybrid Programming Modelsmentioning

confidence: 99%

A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

Basloom¹,

Dahab²,

AL-Ghamdi³

et al. 2023

Computers, Materials &Amp; Continua

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“…Cudagrind utiliza teste estrutural para encontrar erros de memoria (BAUMANN; GRACIA, 2014). ACC_TEST é a única ferramenta que busca testar aplicações híbridas, usando MPI e OpenACC em busca de condições de disputa, deadlock e erros de memória (ALGHAMDI;EASSA, 2019;ALGHAMDI et al, 2020;EASSA et al, 2020). Sarkar utiliza análise estática para detectar condições de disputa em CUDA (SARKAR et al, 2018).…”

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Modelo e critérios de teste estrutural para programas CUDA

Luz¹

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As GPUs têm sido amplamente utilizadas na computação de propósito geral para resolver problemas em diversas áreas. Para utilizar esses processadores, é necessário adotar modelos de programação paralela, como o CUDA, que visam simplificar o desenvolvimento de aplicações de propósito geral para serem executadas em GPUs. A despeito das facilidades trazidas por esse modelo, desenvolver aplicações com CUDA não é trivial. Além disso, os desenvolvedores possuem pouca experiência na programação de aplicações paralelas, ocasionando diversos tipos de defeitos. Apesar da necessidade de mitigar defeitos em aplicações CUDA, há poucos critérios de teste estrutural para revelar defeitos desse modelo de programação. Buscando melhorar a qualidade de programas concorrentes CUDA, foi definido um modelo e critérios de teste estrutural para apoiar a atividade de teste, auxiliando na seleção de casos de teste e propiciando a revelação de defeitos. Para validar o modelo e critérios de teste propostos, foi desenvolvido a ferramenta ValiCUDA, que realiza a instrumentação e análise do programa, gerando os elementos requeridos para cada critério de teste. A ferramenta permite executar os programas e avaliar a cobertura alcançada para cada critério. Para avaliar a aplicação dos critérios de teste, foi realizado um experimento com validação estatística, buscando averiguar as métricas de custo, eficácia e strength. No experimento foram inseridos defeitos com base em uma taxonomia de defeitos para avaliar a eficácia dos critérios. Os resultados demonstraram que os critérios de teste propostos são capazes de revelar defeitos em aplicações CUDA e podem auxiliar o testador na atividade de teste deste tipo de aplicação.

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Parallel Hybrid Testing Techniques for the Dual-Programming Models-Based Programs

et al. 2020

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The importance of high-performance computing is increasing, and Exascale systems will be feasible in a few years. These systems can be achieved by enhancing the hardware’s ability as well as the parallelism in the application by integrating more than one programming model. One of the dual-programming model combinations is Message Passing Interface (MPI) + OpenACC, which has several features including increased system parallelism, support for different platforms with more performance, better productivity, and less programming effort. Several testing tools target parallel applications built by using programming models, but more effort is needed, especially for high-level Graphics Processing Unit (GPU)-related programming models. Owing to the integration of different programming models, errors will be more frequent and unpredictable. Testing techniques are required to detect these errors, especially runtime errors resulting from the integration of MPI and OpenACC; studying their behavior is also important, especially some OpenACC runtime errors that cannot be detected by any compiler. In this paper, we enhance the capabilities of ACC_TEST to test the programs built by using the dual-programming models MPI + OpenACC and detect their related errors. Our tool integrated both static and dynamic testing techniques to create ACC_TEST and allowed us to benefit from the advantages of both techniques reducing overheads, enhancing system execution time, and covering a wide range of errors. Finally, ACC_TEST is a parallel testing tool that creates testing threads based on the number of application threads for detecting runtime errors.

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ACC_TEST: Hybrid Testing Approach for OpenACC-Based Programs

Cited by 3 publications

References 14 publications

A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

Modelo e critérios de teste estrutural para programas CUDA

Parallel Hybrid Testing Techniques for the Dual-Programming Models-Based Programs

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