TY - GEN
T1 - A Hierarchical Task Scheduler for Heterogeneous Computing
AU - Miniskar, Narasinga Rao
AU - Liu, Frank
AU - Young, Aaron R.
AU - Chakraborty, Dwaipayan
AU - Vetter, Jeffrey S.
N1 - Funding Information:
This research was supported in part by the DOE Advanced Scientific Computing Research Program Sawtooth Project and the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle LLC for DOE.
Funding Information:
This material is based upon work supported by the US Department of Energy (DOE) Office of Science, Office of Advanced Scientific Computing Research under contract number DE-AC05-00OR22725. This research was supported in part by the DOE Advanced Scientific Computing Research Program Sawtooth Project and the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle LLC for DOE.
Funding Information:
This manuscript has been co-authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan.
Publisher Copyright:
© 2021, UT-Battelle, LLC.
PY - 2021
Y1 - 2021
N2 - 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 × performance improvement on average, while only requires 2.7 % of area overhead.
AB - 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 × performance improvement on average, while only requires 2.7 % of area overhead.
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U2 - 10.1007/978-3-030-78713-4_4
DO - 10.1007/978-3-030-78713-4_4
M3 - Conference contribution
AN - SCOPUS:85111432079
SN - 9783030787127
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 57
EP - 76
BT - High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings
A2 - Chamberlain, Bradford L.
A2 - Chamberlain, Bradford L.
A2 - Varbanescu, Ana-Lucia
A2 - Ltaief, Hatem
A2 - Luszczek, Piotr
PB - Springer Science and Business Media Deutschland GmbH
T2 - 36th International Conference on High Performance Computing, ISC High Performance 2021
Y2 - 24 June 2021 through 2 July 2021
ER -