TY - GEN
T1 - Towards GPU Acceleration of Phonon Computation with ShengBTE
AU - Wei, Yi
AU - You, Xin
AU - Yang, Hailong
AU - Luan, Zhongzhi
AU - Qian, Depei
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/1/15
Y1 - 2020/1/15
N2 - ShengBTE is one of the software packages that are commonly used in the field of phonon computation (e.g., to determine the lattice thermal conductivity). ShengBTE simulates the phonon diffusion by solving the Boltzmann transport equations, which take long execution time to derive the simulation results due to the high computation complexity. This paper mainly focuses on the performance optimization of ShengBTE on GPU. We identify the performance bottlenecks of ShengBTE and propose corresponding optimizations such as loop-carried dependency elimination, hotspot function acceleration on GPU and performance tuning on thread block. The experiment results show that the proposed optimizations significantly improve the performance of ShengBTE, which achieves an average speedup of 9.06x and 13.74x on discrete temperature simulation and continuous temperature simulation respectively without losing accuracy.
AB - ShengBTE is one of the software packages that are commonly used in the field of phonon computation (e.g., to determine the lattice thermal conductivity). ShengBTE simulates the phonon diffusion by solving the Boltzmann transport equations, which take long execution time to derive the simulation results due to the high computation complexity. This paper mainly focuses on the performance optimization of ShengBTE on GPU. We identify the performance bottlenecks of ShengBTE and propose corresponding optimizations such as loop-carried dependency elimination, hotspot function acceleration on GPU and performance tuning on thread block. The experiment results show that the proposed optimizations significantly improve the performance of ShengBTE, which achieves an average speedup of 9.06x and 13.74x on discrete temperature simulation and continuous temperature simulation respectively without losing accuracy.
UR - https://www.scopus.com/pages/publications/85094847582
U2 - 10.1145/3368474.3368487
DO - 10.1145/3368474.3368487
M3 - 会议稿件
AN - SCOPUS:85094847582
T3 - ACM International Conference Proceeding Series
SP - 32
EP - 42
BT - Proceedings of International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2020
PB - Association for Computing Machinery
T2 - 2020 International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2020
Y2 - 15 January 2020 through 17 January 2020
ER -