|
|
MilkyWay-2 supercomputer: system and application |
Xiangke LIAO1,2,*( ),Liquan XIAO2,Canqun YANG1,2,Yutong LU2 |
1. Science and Technology on Parallel and Distributed Processing Laboratory, National University of Defense Technology, Changsha 410073, China 2. College of Computer, National University of Defense Technology, Changsha 410073, China |
|
|
Abstract On June 17, 2013, MilkyWay-2 (Tianhe-2) supercomputer was crowned as the fastest supercomputer in the world on the 41th TOP500 list. This paper provides an overview of the MilkyWay-2 project and describes the design of hardware and software systems. The key architecture features of MilkyWay-2 are highlighted, including neo-heterogeneous compute nodes integrating commodity-off-the-shelf processors and accelerators that share similar instruction set architecture, powerful networks that employ proprietary interconnection chips to support the massively parallel message-passing communications, proprietary 16-core processor designed for scientific computing, efficient software stacks that provide high performance file system, emerging programming model for heterogeneous systems, and intelligent system administration. We perform extensive evaluation with wide-ranging applications from LINPACK and Graph500 benchmarks to massively parallel software deployed in the system.
|
Keywords
MilkyWay-2 supercomputer
petaflops computing
neo-heterogeneous architecture
interconnect network
heterogeneous programing model
system management
benchmark optimization
performance evaluation
|
Corresponding Author(s):
Xiangke LIAO
|
Issue Date: 24 June 2014
|
|
1 |
YangX J, LiaoX K, LuK, HuQ F, SongJ Q, SuJ S. The Tianhe-1a su-percomputer: its hardware and software. Journal of Computer Science and Technology, 2011, 26(3): 344-351 doi: 10.1007/s02011-011-1137-8
|
2 |
ZhangH, WangK, ZhangJ, WuN, DaiY. A fast and fair shared buffer for high-radix router. Journal of Circuits, Systems, and Computers, 2013
|
3 |
KirkD. Nvidia cuda software and GPU parallel computing architecture. In: Proceedings of the 6th International Symposium on Memory Management. 2007, 103-104
|
4 |
SherlekarS. Tutorial: Intel many integrated core (MIC) architecture. In: Proceedings of the 18th IEEE International Conference on Parallel and Distributed Systems. 2012, 947
|
5 |
GasterB, HowesL, KaeliD R, MistryP, SchaaD. Heterogeneous Computing with OpenCL. Morgan Kaufmann Publishers Inc., 2011
|
6 |
LeeS, VetterJ S. Early evaluation of directive-based GPU programming models for productive exascale computing. In: Proceedings of the 2012 International Conference for High Performance Computing, Networking, Storage and Analysis. 2012, 1-11
|
7 |
WienkeS, SpringerP, TerbovenC, MeyD. Openacc: first experiences with real-world applications. In: Proceedings of the 18th International Conference on Parallel Processing. 2012, 859-870
|
8 |
PGI Accelerator Compilers. Portland Group Inc, 2011
|
9 |
YangX L, TangT, WangG B, JiaJ, XuX H. MPtoStream: an openMP compiler for CPU-GPU heterogeneous parallel systems. Science China Information Sciences, 2012, 55(9): 1961-1971 doi: 10.1007/s11432-011-4342-4
|
10 |
DolbeauR, BihanS, BodinF. Hmpp: a hybrid multi-core parallel programming environment. In: Proceedings of the 2007 Workshop on General Purpose Processing on Graphics Processing Units. 2007, 1-5
|
11 |
ChecconiF, PetriniF, WillcockJ, LumsdaineA, ChoudhuryA R, SabharwalY. Breaking the speed and scalability barriers for graph exploration on distributed-memory machines. In: Proceedings of the 2012 International Conference for High Performance Computing, Networking, Storage and Analysis. 2012, 1-12 doi: 10.1109/SC.2012.25
|
12 |
BeamerS, BuluçA, AsanovicK, PattersonD. Distributed memory breadth-first search revisited: enabling bottom-up search. In: Proceedings of the 27th IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum. 2013, 1618-1627
|
13 |
SubramaniamS, MehrotraM, GuptaD. Virtual high throughput screening (VHIS)–a perspective. Bioinformation, 2007, 3(1): 14-17 doi: 10.6026/97320630003014
|
14 |
TanrikuluY, KrügerB, ProschakE. The holistic integration of virtual screening in drug discovery. Drug Discovery Today, 2013, 18(7): 358-364 doi: 10.1016/j.drudis.2013.01.007
|
15 |
ZhangX, WongS E, LightstoneF C. Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines. Journal of Computational Chemistry, 2013, 34(11): 915-927 doi: 10.1002/jcc.23214
|
16 |
LangP T, BrozellS R, MukherjeeS, PettersenE F, MengE C, ThomasV, RizzoR C, CaseD A, JamesT L, KuntzI D. Dock 6: combining techniques to model RNA–small molecule complexes. RNA, 2009, 15(6): 1219-1230 doi: 10.1261/rna.1563609
|
17 |
GaoZ, LiH, ZhangH, LiuX, KangL, LuoX, ZhuW, ChenK, WangX, JiangH. PDTD: a web-accessible protein database for drug target identification. BMC Bioinformatics, 2008, 9(1): 104 doi: 10.1186/1471-2105-9-104
|
18 |
YangC, XueW, FuH, GanL, LiL, XuY, LuY, SunJ, YangG, ZhengW. A peta-scalable CPU-GPU algorithm for global atmospheric simulations. In: Proceedings of the 18th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. 2013, 1-12
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|