DataRaceOnAccelerator – A Micro-benchmark Suite for Evaluating Correctness Tools Targeting Accelerators

Schmitz, Adrian; Protze, Joachim; Yu, Lechen; Schwitanski, Simon; Müller, Matthias S.

doi:10.1007/978-3-030-48340-1_19

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…In particular, we used the Java benchmarks from the IBM Contest suite [19], Java Grande suite [60], DaCapo [9], and SIR [16]. In addition, we used OpenMP benchmark programs, whose execution lenghts and number of threads can be tuned, from DataRaceOnAccelerator [54], DataRaceBench [33], OmpSCR [17] and the NAS parallel benchmarks [6], as well as large OpenMP applications contained in the following benchmark suites: CORAL [1, 2], ECP proxy applications [3], and Mantevo project [4]. Each benchmark was instrumented and executed in order to log a single concurrent trace, using the tools RV-Predict [51] (for Java programs) and ThreadSanitizer [56] (for OpenMP programs).…”

Section: Methodsmentioning

confidence: 99%

A tree clock data structure for causal orderings in concurrent executions

Mathur

Pavlogiannis

Tunç

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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Dynamic techniques are a scalable and effective way to analyze concurrent programs. Instead of analyzing all behaviors of a program, these techniques detect errors by focusing on a single program execution. Often a crucial step in these techniques is to define a causal ordering between events in the execution, which is then computed using vector clocks, a simple data structure that stores logical times of threads. The two basic operations of vector clocks, namely join and copy, require Θ(𝑘) time, where 𝑘 is the number of threads. Thus they are a computational bottleneck when 𝑘 is large.In this work, we introduce tree clocks, a new data structure that replaces vector clocks for computing causal orderings in program executions. Joining and copying tree clocks takes time that is roughly proportional to the number of entries being modified, and hence the two operations do not suffer the a-priori Θ(𝑘) cost per application. We show that when used to compute the classic happens-before (HB) partial order, tree clocks are optimal, in the sense that no other data structure can lead to smaller asymptotic running time. Moreover, we demonstrate that tree clocks can be used to compute other partial orders, such as schedulable-happens-before (SHB) and the standard Mazurkiewicz (MAZ) partial order, and thus are a versatile data structure. Our experiments show that just by replacing vector clocks with tree clocks, the computation becomes from 2.02× faster (MAZ) to 2.66× (SHB) and 2.97× (HB) on average per benchmark. These results illustrate that tree clocks have the potential to become a standard data structure with wide applications in concurrent analyses. CCS CONCEPTS• Software and its engineering → Software verification and validation; • Theory of computation → Theory and algorithms for application domains; Program analysis.

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Section: Methodsmentioning

confidence: 99%

A tree clock data structure for causal orderings in concurrent executions

Mathur

Pavlogiannis

Tunç

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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“…Also, each author uses a different set of benchmarks. It would be interesting to test all the mentioned tools with the benchmark suite created by the work of Schmitz et al [34], for a fair comparison between tools.…”

Section: Available Solutionsmentioning

confidence: 99%

“…In the papers presenting the various tools, those tools are compared with each other to show that for specific kernels, the new tool is, at that point in time, the best. It would be better to use a standard benchmark suite, like the suite by Schmitz et al [34], which is uniformly used and addresses the errors we mention in this paper. Additionally, it should support all the CUDA and OpenCL features.…”

Section: Research Directionsmentioning

confidence: 99%

Formal Methods for GPGPU Programming: Is the Demand Met?

Haak

Wijs

Brand

et al. 2020

Lecture Notes in Computer Science

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Over the years, researchers have developed many formal method tools to support software development. However, hardly any studies are conducted to determine whether the actual problems developers encounter are sufficiently addressed. For the relatively young field of GPU programming, we would like to know whether the tools developed so far are sufficient, or whether some problems still need attention. To this end, we first look at what kind of problems programmers encounter in OpenCL and CUDA. We gather problems from Stack Overflow and categorise them with card sorting. We find that problems related to memory, synchronisation of threads, threads in general and performance are essential topics. Next, we look at (verification) tools in industry and research, to see how these tools addressed the problems we discovered. We think many problems are already properly addressed, but there is still a need for easy to use sound tools. Alternatively, languages or programming styles can be created, that allows for easier checking for soundness.

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