MPI Thread-Level Checking for MPI+OpenMP Applications

Saillard, Emmanuelle; Carribault, Patrick; Barthou, Denis

doi:10.1007/978-3-662-48096-0_3

Cited by 3 publications

(6 citation statements)

References 17 publications

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“…These variations include testing tools or detection for a specific type of errors or a different type of errors. Some studies focus on using static testing techniques [25][26][27][28] to detect errors by analyzing the source code and find real as well as potential run-time errors [29,30]; dynamic testing techniques [31,32] to detect errors after execution and at run-time; or hybrid testing techniques [33][34][35]. Also, detecting errors in programming models also varied from the testing tool for single level programming model to the tri-level programming model.…”

Section: Related Workmentioning

confidence: 99%

Parallel Hybrid Testing Tool for Applications Developed by Using MPI + OpenACC Dual-Programming Model

Alghamdi¹,

Eassa²

2019

Adv. sci. technol. eng. syst. j.

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Building massively parallel applications has become increasingly important with coming Exascale related technologies. For building these applications, a combination of programming models is needed to increase the system's parallelism. One of these combinations is the dual-programming model (MPI+X) which has many structures that increase parallelism in heterogeneous systems that include CPUs and GPUs. MPI + OpenACC programming model has many advantages and features that increase parallelism with respect heterogeneous architecture and support different platform with more performance, productivity, and programmability. The main problem in building systems with different programming models that it is a hard job for programmers and it is more error-prone, which is not easy to test. Also, testing parallel applications is a difficult task, because of the non-determined behavior of the parallel application. Even after detecting the errors and modifying the source code, it is not easy to determine whether the errors have been corrected or remain hidden. Furthermore, integrating two different programming models inside the same application makes it even more difficult to test. Also, the misusage of OpenACC can lead to several run-time errors that compilers cannot detect, and the programmers will not know about them. To solve this problem, we proposed a parallel hybrid testing tool for detecting run-time errors for systems implemented in C++ and MPI + OpenACC. The hybrid techniques combine static and dynamic testing techniques for detecting real and potential run-time errors by analyzing the source code and during run time. Using parallel hybrid techniques will enhance the testing time and cover a wide range of errors. Also, we propose a new assertion language for helping in detecting potential run-time errors. Finally, to the best of our knowledge, identifying and classifying OpenACC errors has not been done before, and there is no parallel testing tool designed to test applications programmed by using the dualprogramming model MPI + OpenACC or the single-programming models OpenACC.

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Section: Related Workmentioning

confidence: 99%

Parallel Hybrid Testing Tool for Applications Developed by Using MPI + OpenACC Dual-Programming Model

Alghamdi¹,

Eassa²

2019

Adv. sci. technol. eng. syst. j.

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“…If deadlocks are about to occur at runtime, the program is stopped and PARCOACH returns error messages with compilation information. This section describes the following new features of PARCOACH: (i) detection of the minimal MPI thread-level support required by an MPI+OpenMP application (see [9] for more details) and (ii) checking misuse of MPI blocking and nonblocking collectives in a multi-threaded context (extension of [10]). …”

Section: Parcoach Static and Dynamic Analyses For Hybrid Applicationsmentioning

confidence: 99%

“…Then, with a depth-first search traversal, we associate a parallelism word to each node. As defined in [9], a parallelism word is the sequence of OpenMP parallel constructs (P:parallel, S:single, M:master and B:barrier for implicit and explicit barriers) surrounding a node from the beginning of the function to the node. The analysis detects CFG nodes containing MPI calls associated to parallelism words defining a multithreaded context and forbidden concurrent calls.…”

Section: Mpi Thread-level Checkingmentioning

confidence: 99%

“…A parallelism word defines a For this part, it is not necessary to seperate single from master regions. So the finite-state automaton in [9] is simplified into the automaton presented Figure 4. It recognizes the language of parallelism words corresponding to monothreaded regions.…”

Section: Mpi Collective Communication Verificationmentioning

confidence: 99%

“…In this paper, we propose an extension of PARCOACH to hybrid MPI+OpenMP applications and an interprocedural analysis to improve the bug detection through a whole program. This work is based on [9] and extends [10] with more details and an interprocedural analysis. To the best of our knowledge, only Marmot [3] is able to detect errors in MPI+OpenMP programs.…”

Section: Introductionmentioning

confidence: 99%

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PARCOACH Extension for Hybrid Applications with Interprocedural Analysis

Saillard¹,

Brunie²,

Carribault³

et al. 2016

Tools for High Performance Computing 2015

Self Cite

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Supercomputers are rapidly evolving with now millions of processing units, posing the questions of their programmability. Despite the emergence of more widespread and functional programming models, developing correct and effective parallel applications still remains a complex task. Although debugging solutions have emerged to address this issue, they often come with restrictions. Furthermore, programming model evolutions stress the requirement for a validation tool able to handle hybrid applications. Indeed, as current scientific applications mainly rely on MPI (Message-Passing Interface), new hardwares designed with a larger node-level parallelism advocate for an MPI+X solution with X a shared-memory model like OpenMP. But integrating two different approaches inside the same application can be error-prone leading to complex bugs. In an MPI+X program, not only the correctness of MPI should be ensured but also its interactions with the multi-threaded model. For example, identical MPI collective operations cannot be performed by multiple non-synchronized threads. In this paper, we present an extension of the PARallel COntrol flow Anomaly CHecker (PARCOACH) to enable verification of hybrid HPC applications. Relying on a GCC plugin that combines static and dynamic analysis, the first pass statically verifies the thread level required by an MPI+OpenMP application and outlines execution paths leading to potential deadlocks. Based on this analysis, the code is selectively instrumented, displaying an error and interrupting all processes if the actual scheduling leads to a deadlock situation.Emmanuelle Saillard CEA, DAM,

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A Parallel Hybrid-Testing Tool Architecture for a Dual-Programming Model

Alghamdi¹,

Elbouraey²

2019

IJACSA

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High-Performance Computing (HPC) recently has become important in several sectors, including the scientific and manufacturing fields. The continuous growth in building more powerful super machines has become noticeable, and the Exascale supercomputer will be feasible in the next few years. As a result, building massively parallel systems becomes even more important to keep up with the upcoming Exascale-related technologies. For building such systems, a combination of programming models is needed to increase the system's parallelism, especially dual and tri-level programming models to increase parallelism in heterogeneous systems that include CPUs and GPUs. There are several combinations of the dualprogramming model; one of them is MPI+ OpenACC. This combination has several features that increase the application's parallelism concerning heterogeneous architecture and support different platforms with more performance, productivity, and programmability. However, building systems with different programming models are error-prone and difficult and are also hard to test. Also, testing parallel applications is already a difficult task because parallel errors are hard to detect due to the non-determined behavior of the parallel application. Integrating more than one programming model inside the same application makes even it more difficult to test because this integration could come with a new type of errors. Our main contribution is to identify and categorize OpenACC run-time errors and determine their causes with a brief explanation for the first time in research. Also, we proposed a solution for detecting run-time errors in application implemented in the dual-programming model. Our solution based on using hybrid testing techniques to discover real and potential run-time errors. Finally, to the best of our knowledge, there is no parallel testing tool built to test applications programmed by using the dual-programming model MPI + OpenACC or any tri-level programming model or even the OpenACC programming model to detect their run-time errors. Also, OpenACC errors have not been classified or identified before.

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MPI Thread-Level Checking for MPI+OpenMP Applications

Cited by 3 publications

References 17 publications

Parallel Hybrid Testing Tool for Applications Developed by Using MPI + OpenACC Dual-Programming Model

Parallel Hybrid Testing Tool for Applications Developed by Using MPI + OpenACC Dual-Programming Model

PARCOACH Extension for Hybrid Applications with Interprocedural Analysis

A Parallel Hybrid-Testing Tool Architecture for a Dual-Programming Model

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