TY - GEN
T1 - Refactoring the molecular docking simulation for heterogeneous, manycore processors systems
AU - Chen, Junshi
AU - Lin, Han
AU - Liang, Weihao
AU - Yu, Yang
AU - Han, Wenting
AU - An, Hong
AU - Chen, Yong
AU - Liu, Xin
PY - 2018/5/25
Y1 - 2018/5/25
N2 - This paper presents a scalable design and implementation of the molecular docking application DOCK for a large-scale high performance computing system, the Sunway TaihuLight supercomputer, which provisions a heterogeneous, manycore processor architecture that consists of management processing elements (MPEs) and clusters of computing processing elements (CPEs). The key innovation is a novel refactoring of DOCK on the CPEs. Optimization techniques for data redundancy minimization to fit data in cache, software-controlled prefetching into scratchpads, memory access coalescing, software caches, vectorization and loop unrolling are employed to improve the exploitation of the computational resources. For a single docking process, the refactored version using both the MPE and CPE cluster achieved 260x to 402x speedup compared against the original ported version using MPE only. To scale the DOCK to the full Sunway Taihulight system with 10,649,600 cores (including all MPE and CPE cores), we present an MPI communication domain partition scheme as well. For docking 9 million small compounds to a Zika virus target protein, we manage to scale to 131,072 MPEs, and 8,388,608 CPEs, with a total of 8,519,680 cores.
AB - This paper presents a scalable design and implementation of the molecular docking application DOCK for a large-scale high performance computing system, the Sunway TaihuLight supercomputer, which provisions a heterogeneous, manycore processor architecture that consists of management processing elements (MPEs) and clusters of computing processing elements (CPEs). The key innovation is a novel refactoring of DOCK on the CPEs. Optimization techniques for data redundancy minimization to fit data in cache, software-controlled prefetching into scratchpads, memory access coalescing, software caches, vectorization and loop unrolling are employed to improve the exploitation of the computational resources. For a single docking process, the refactored version using both the MPE and CPE cluster achieved 260x to 402x speedup compared against the original ported version using MPE only. To scale the DOCK to the full Sunway Taihulight system with 10,649,600 cores (including all MPE and CPE cores), we present an MPI communication domain partition scheme as well. For docking 9 million small compounds to a Zika virus target protein, we manage to scale to 131,072 MPEs, and 8,388,608 CPEs, with a total of 8,519,680 cores.
KW - Heterogeneous
KW - Manycore
KW - Molecular docking
KW - Optimization
KW - Sunway TaihuLight Supercomputer
UR - http://www.scopus.com/inward/record.url?scp=85048358247&partnerID=8YFLogxK
U2 - 10.1109/ISPA/IUCC.2017.00157
DO - 10.1109/ISPA/IUCC.2017.00157
M3 - Conference contribution
AN - SCOPUS:85048358247
T3 - Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
SP - 1031
EP - 1038
BT - Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
A2 - Martinez, Gregorio
A2 - Hill, Richard
A2 - Fox, Geoffrey
A2 - Mueller, Peter
A2 - Wang, Guojun
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 December 2017 through 15 December 2017
ER -