Modeling Task Mapping for Data-intensive Applications in Heterogeneous Systems
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2022
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| Acceso en línea: | |
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| _version_ | 1866918444043075584 |
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| author | Wilhelm, Martin Geppert, Hanna Drewes, Anna Pionteck, Thilo |
| author_facet | Wilhelm, Martin Geppert, Hanna Drewes, Anna Pionteck, Thilo |
| contents | We introduce a new model for the task mapping problem to aid in the systematic design of algorithms for heterogeneous systems including, but not limited to, CPUs, GPUs and FPGAs. A special focus is set on the communication between the devices, its influence on parallel execution, as well as on device-specific differences regarding parallelizability and streamability. We show how this model can be utilized in different system design phases and present two novel mixed-integer linear programs to demonstrate the usage of the model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2208_06321 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Modeling Task Mapping for Data-intensive Applications in Heterogeneous Systems Wilhelm, Martin Geppert, Hanna Drewes, Anna Pionteck, Thilo Distributed, Parallel, and Cluster Computing Optimization and Control We introduce a new model for the task mapping problem to aid in the systematic design of algorithms for heterogeneous systems including, but not limited to, CPUs, GPUs and FPGAs. A special focus is set on the communication between the devices, its influence on parallel execution, as well as on device-specific differences regarding parallelizability and streamability. We show how this model can be utilized in different system design phases and present two novel mixed-integer linear programs to demonstrate the usage of the model. |
| title | Modeling Task Mapping for Data-intensive Applications in Heterogeneous Systems |
| topic | Distributed, Parallel, and Cluster Computing Optimization and Control |
| url | https://arxiv.org/abs/2208.06321 |