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Conference Papers Year : 2022

Decentralized in-order execution of a sequential task-based code for shared-memory architectures

Abstract

The hardware complexity of modern machines makes the design of adequate programming models crucial for jointly ensuring performance, portability, and productivity in high-performance computing (HPC). Sequential task-based programming models paired with advanced runtime systems allow the programmer to write a sequential algorithm independently of the hardware architecture in a productive and portable manner, and let a third party software layer-the runtime system-deal with the burden of scheduling a correct, parallel execution of that algorithm to ensure performance. Many HPC algorithms have successfully been implemented following this paradigm, as a testimony of its effectiveness. Developing algorithms that specifically require fine-grained tasks along this model is still considered prohibitive, however, due to per-task management overhead [1], forcing the programmer to resort to a less abstract, and hence more complex "task+X" model. We thus investigate the possibility to offer a tailored execution model, trading dynamic mapping for efficiency by using a decentralized, conservative in-order execution of the task flow, while preserving the benefits of relying on the sequential taskbased programming model. We propose a formal specification of the execution model as well as a prototype implementation, which we assess on a shared-memory multicore architecture with several synthetic workloads. The results show that under the condition of a proper task mapping supplied by the programmer, the pressure on the runtime system is significantly reduced and the execution of fine-grained task flows is much more efficient.
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Dates and versions

hal-03896030 , version 1 (13-12-2022)

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Charly Castes, Emmanuel Agullo, Olivier Aumage, Emmanuelle Saillard. Decentralized in-order execution of a sequential task-based code for shared-memory architectures. IPDPSW 2022 - IEEE International Parallel and Distributed Processing Symposium Workshops, May 2022, Lyon, France. pp.552-561, ⟨10.1109/IPDPSW55747.2022.00095⟩. ⟨hal-03896030⟩

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