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Erschienen in:
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2021 | OriginalPaper | Buchkapitel

A Hierarchical Task Scheduler for Heterogeneous Computing

verfasst von : Narasinga Rao Miniskar, Frank Liu, Aaron R. Young, Dwaipayan Chakraborty, Jeffrey S. Vetter

Erschienen in: High Performance Computing

Verlag: Springer International Publishing

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Abstract

Heterogeneous computing is one of the future directions of HPC. Task scheduling in heterogeneous computing must balance the challenge of optimizing the application performance and the need for an intuitive interface with the programming run-time to maintain programming portability. The challenge is further compounded by the varying data communication time between tasks. This paper proposes RANGER, a hardware-assisted task-scheduling framework. By integrating RISC-V cores with accelerators, the RANGER scheduling framework divides scheduling into global and local levels. At the local level, RANGER further partitions each task into fine-grained subtasks to reduce the overall makespan. At the global level, RANGER maintains the coarse granularity of the task specification, thereby maintaining programming portability. The extensive experimental results demonstrate that RANGER achieves a \(12.7\times \) performance improvement on average, while only requires \(2.7\%\) of area overhead.

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Vorheriges Kapitel Lessons Learned from Accelerating Quicksilver on Programmable Integrated Unified Memory Architecture (PIUMA) and How That’s Different from CPU
Nächstes Kapitel Auto-Precision Scaling for Distributed Deep Learning
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Metadaten
Titel
A Hierarchical Task Scheduler for Heterogeneous Computing
verfasst von
Narasinga Rao Miniskar
Frank Liu
Aaron R. Young
Dwaipayan Chakraborty
Jeffrey S. Vetter
Copyright-Jahr
2021
Buch
High Performance Computing

Print ISBN: 978-3-030-78712-7

Electronic ISBN: 978-3-030-78713-4

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-3-030-78713-4_4

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