PEPS plus plus : Towards Extreme-Scale Simulations of Strongly Correlated Quantum Many-Particle Models on Sunway TaihuLight

被引:17
作者
He, Lixin [1 ]
An, Hong [2 ]
Yang, Chao [3 ,4 ]
Wang, Fei [5 ]
Chen, Junshi [2 ]
Wang, Chao [1 ]
Liang, Weihao [2 ]
Dong, Shaojun [1 ]
Sun, Qiao [6 ]
Han, Wenting [2 ]
Liu, Wenyuan [1 ]
Han, Yongjian [1 ]
Yao, Wenjun [2 ]
机构
[1] Univ Sci & Technol China, CAS Key Lab Quantum Informat, Hefei 230026, Anhui, Peoples R China
[2] Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei 230026, Anhui, Peoples R China
[3] Peking Univ, Sch Math Sci & NELVT, Sch Elect Engn & Comp Sci, CCSE, Beijing 100871, Peoples R China
[4] Peking Univ, Sch Math Sci & NELVT, Sch Elect Engn & Comp Sci, CAPT, Beijing 100871, Peoples R China
[5] Natl Res Ctr Parallel Comp Engn & Technol, Beijing 100190, Peoples R China
[6] Chinese Acad Sci, Inst Software, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
Quantum spin liquid; PEPS plus; Sunway Taihulight; MATRIX RENORMALIZATION-GROUP; PRODUCT STATES; SYSTEMS; ANYONS;
D O I
10.1109/TPDS.2018.2848618
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The study of strongly frustrated magnetic systems has drawn great attentions from both theoretical and experimental physics. Efficient simulations of these models are essential for understanding their exotic properties. Here we present PEPS++, a novel computational paradigm for simulating frustrated magnetic systems and other strongly correlated quantum many-body systems. PEPS++ can accurately solve these models at the extreme scale with low cost and high scalability on modern heterogeneous supercomputers. We implement PEPS++ on Sunway TaihuLight based on a carefully designed tensor computation library for manipulating high-rank tensors and optimize it by invoking various high-performance matrix and tensor operations. By solving a 2D strongly frustrated J(1)-J(2) model with over ten million cores, PEPS++ demonstrates the capability of simulating strongly correlated quantum many-body problems at unprecedented scales with accuracy and time-to-solution far beyond the previous state of the art.
引用
收藏
页码:2838 / 2848
页数:11
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