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

Alghamdi, Ahmed Mohammed; Eassa, Fathy; Khamakhem, Maher Ali; AL-Ghamdi, Abdullah S. AL-Malaise; Alfakeeh, Ahmed S.; Alshahrani, Abdullah; Alarood, Ala Abdulsalam

doi:10.3390/sym12091555

Cited by 4 publications

(5 citation statements)

References 35 publications

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“…To our knowledge, there is currently no testing tool based on temporal logic designed to detect runtime errors in hybrid programming models. Furthermore, the proposed tools represented by [44,45,55] utilize simple assert statements to detect runtime errors in hybrid programming models. Table 6 presents a detailed comparison between our proposed tool architecture and that of other tools.…”

Section: Discussionmentioning

confidence: 99%

Temporal-Logic-Based Testing Tool Architecture for Dual-Programming Model Systems

Saad,

Fadel,

Alzamzami

et al. 2024

Computers

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Today, various applications in different domains increasingly rely on high-performance computing (HPC) to accomplish computations swiftly. Integrating one or more programming models alongside the used programming language enhances system parallelism, thereby improving its performance. However, this integration can introduce runtime errors such as race conditions, deadlocks, or livelocks. Some of these errors may go undetected using conventional testing techniques, necessitating the exploration of additional methods for enhanced reliability. Formal methods, such as temporal logic, can be useful for detecting runtime errors since they have been widely used in real-time systems. Additionally, many software systems must adhere to temporal properties to ensure correct functionality. Temporal logics indeed serve as a formal frame that takes into account the temporal aspect when describing changes in elements or states over time. This paper proposes a temporal-logic-based testing tool utilizing instrumentation techniques designed for a dual-level programming model, namely, Message Passing Interface (MPI) and Open Multi-Processing (OpenMP), integrated with the C++ programming language. After a comprehensive study of temporal logic types, we found and proved that linear temporal logic is well suited as the foundation for our tool. Notably, while the tool is currently in development, our approach is poised to effectively address the highlighted examples of runtime errors by the proposed solution. This paper thoroughly explores various types and operators of temporal logic to inform the design of the testing tool based on temporal properties, aiming for a robust and reliable system.

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Section: Discussionmentioning

confidence: 99%

Temporal-Logic-Based Testing Tool Architecture for Dual-Programming Model Systems

Saad,

Fadel,

Alzamzami

et al. 2024

Computers

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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%

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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“…Moreover, the utilization of hybrid programming models enhances the efficiency of achieving exa-scale computing capabilities, necessitating the development of programming models capable of effectively supporting massively parallel systems. The programming models can be categorized into three tiers: the single-level programming model, which includes MPI; the dual-level programming model, which combines MPI and OpenMP; and the tri-level programming model, which incorporates MPI, OpenMP, and CUDA [9].…”

Section: Introductionmentioning

confidence: 99%

Predicting Software Defects in Hybrid MPI and OpenMP Parallel Programs Using Machine Learning

Althiban,

Alharbi,

Al Khuzayem

et al. 2023

Electronics

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High-performance computing (HPC) and its supercomputers are essential for solving the most difficult issues in many scientific computing domains. The proliferation of computational resources utilized by HPC systems has resulted in an increase in the associated error rates. As such, modern HPC systems promote a hybrid programming style that integrates the message-passing interface (MPI) and open multi-processing (OpenMP). However, this integration often leads to complex defects, such as deadlocks and race conditions, that are challenging to detect and resolve. This paper presents a novel approach: using machine learning algorithms to predict defects in C++-based systems by employing hybrid MPI and OpenMP models. We focus on employing a balanced dataset to enhance prediction accuracy and reliability. Our study highlights the effectiveness of the support vector machine (SVM) classifier, enhanced with term frequency (TF) and recursive feature elimination (RFE) techniques, which demonstrates superior accuracy and performance in defect prediction when compared to other classifiers. This research contributes significantly to the field by providing a robust method for early defect detection in hybrid programming environments, thereby reducing development time, costs and improving the overall reliability of HPC systems.

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

Cited by 4 publications

References 35 publications

Temporal-Logic-Based Testing Tool Architecture for Dual-Programming Model Systems

Temporal-Logic-Based Testing Tool Architecture for Dual-Programming Model Systems

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

Predicting Software Defects in Hybrid MPI and OpenMP Parallel Programs Using Machine Learning

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