Yongjian Han

dblp:219/8688 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 81% GPUs and heterogeneous computing · 19%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering › computational physics
quantum many-body simulation
0.312018
PEPS++: Towards Extreme-Scale Simulations of Strongly Correlated Quantum Many-Particle Models on Sunway TaihuLight · IEEE Trans. Parallel Distributed Syst. 2018
High-performance computing › large-scale simulation
extreme-scale simulation
0.312018
PEPS++: Towards Extreme-Scale Simulations of Strongly Correlated Quantum Many-Particle Models on Sunway TaihuLight · IEEE Trans. Parallel Distributed Syst. 2018
GPUs and heterogeneous computing
heterogeneous supercomputing
0.112018
PEPS++: Towards Extreme-Scale Simulations of Strongly Correlated Quantum Many-Particle Models on Sunway TaihuLight · IEEE Trans. Parallel Distributed Syst. 2018
High-performance computing › supercomputing
sunway taihulight
0.112018
PEPS++: Towards Extreme-Scale Simulations of Strongly Correlated Quantum Many-Particle Models on Sunway TaihuLight · IEEE Trans. Parallel Distributed Syst. 2018

Methods — techniques the papers use, named apart from their topics

tensor computation · 0.7high-performance matrix operations · 0.7
YearPublicationVenuePosition
2018 PEPS++: Towards Extreme-Scale Simulations of Strongly Correlated Quantum Many-Particle Models on Sunway TaihuLight
abstract
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.
Lixin He, Hong An, Chao Yang 0002, Junshi Chen 0003, Weihao Liang, Shao-Jun Dong, Qiao Sun 0005, Wenting Han, Yongjian Han, Wenjun Yao
IEEE Trans. Parallel Distributed Syst.12