TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909286589792256 |
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| author | Pauloski, J. Gregory Hayot-Sasson, Valerie Gonthier, Maxime Hudson, Nathaniel Pan, Haochen Zhou, Sicheng Foster, Ian Chard, Kyle |
| author_facet | Pauloski, J. Gregory Hayot-Sasson, Valerie Gonthier, Maxime Hudson, Nathaniel Pan, Haochen Zhou, Sicheng Foster, Ian Chard, Kyle |
| contents | Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tasks into a single, unified application designed to achieve a computational goal. Task-based execution frameworks abstract the parallel execution of an application's tasks on arbitrary hardware. Research into these task executors has accelerated as computational sciences increasingly need to take advantage of parallel compute and/or heterogeneous hardware. However, the lack of evaluation standards makes it challenging to compare and contrast novel systems against existing implementations. Here, we introduce TaPS, the Task Performance Suite, to support continued research in parallel task executor frameworks. TaPS provides (1) a unified, modular interface for writing and evaluating applications using arbitrary execution frameworks and data management systems and (2) an initial set of reference synthetic and real-world science applications. We discuss how the design of TaPS supports the reliable evaluation of frameworks and demonstrate TaPS through a survey of benchmarks using the provided reference applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_07236 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks Pauloski, J. Gregory Hayot-Sasson, Valerie Gonthier, Maxime Hudson, Nathaniel Pan, Haochen Zhou, Sicheng Foster, Ian Chard, Kyle Distributed, Parallel, and Cluster Computing Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tasks into a single, unified application designed to achieve a computational goal. Task-based execution frameworks abstract the parallel execution of an application's tasks on arbitrary hardware. Research into these task executors has accelerated as computational sciences increasingly need to take advantage of parallel compute and/or heterogeneous hardware. However, the lack of evaluation standards makes it challenging to compare and contrast novel systems against existing implementations. Here, we introduce TaPS, the Task Performance Suite, to support continued research in parallel task executor frameworks. TaPS provides (1) a unified, modular interface for writing and evaluating applications using arbitrary execution frameworks and data management systems and (2) an initial set of reference synthetic and real-world science applications. We discuss how the design of TaPS supports the reliable evaluation of frameworks and demonstrate TaPS through a survey of benchmarks using the provided reference applications. |
| title | TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2408.07236 |