Large Scale Quantum Chemistry with Tensor Processing Units

被引：19

作者：

Pederson, Ryan ^{[2
,3
,9
]}

Kozlowski, John ^{[1
,2
,3
]}

Song, Ruyi ^{[2
,3
,4
]}

Beall, Jackson ^{[3
,5
]}

Ganahl, Martin ^{[3
]}

Hauru, Markus ^{[3
,6
]}

Lewis, Adam G. M. ^{[3
,5
]}

Yao, Yi ^{[7
]}

Mallick, Shrestha Basu ^{[2
,3
]}

Blum, Volker ^{[4
,7
]}

Vidal, Guifre ^{[2
,3
,8
]}

机构：

[1] Univ Calif Irvine, Dept Chem, Irvine, CA 92617 USA

[2] X Moonshot Factory, Mountain View, CA 94043 USA

[3] SandboxAlphabet, Mountain View, CA 94043 USA

[4] Duke Univ, Dept Chem, Durham, NC 27708 USA

[5] SandboxAQ, Palo Alto, CA 94304 USA

[6] Alan Turing Inst, London NW1 2DB, England

[7] Duke Univ, Thomas Lord Dept Mech Engn & Mat Sci, Durham, NC 27708 USA

[8] Google Quantum AI, Mountain View, CA 94043 USA

[9] Univ Calif Irvine, Dept Phys & Astron, Irvine, CA 92617 USA

来源：

JOURNAL OF CHEMICAL THEORY AND COMPUTATION | 2023年 / 19卷 / 01期

基金：

美国国家科学基金会;

关键词：

DENSITY-FUNCTIONAL CALCULATIONS; PERFORMANCE; ORIGINS;

D O I：

10.1021/acs.jctc.2c00876

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

We demonstrate the use of Googles cloud-based Tensor Processing Units (TPUs) to accelerate and scale up conventional (cubic scaling) density functional theory (DFT) calculations. Utilizing 512 TPU cores, we accomplish the largest such DFT computation to date, with 247848 orbitals, corresponding to a cluster of 10327 water molecules with 103270 electrons, all treated explicitly. Our work thus paves the way toward accessible and systematic use of conventional DFT, free of any system-specific constraints, at unprecedented scales.

引用

页码：25 / 32

页数：8

共 50 条

[31] Accelerating Applications using Edge Tensor Processing Units
Hsu, Kuan-Chieh
Tseng, Hung-Wei
SC21: INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS, 2021,
[32] Large scale tensor analysis by computer
Christensen, SM
COMPUTER PHYSICS COMMUNICATIONS, 1998, 115 (2-3) : 245 - 263
[33] Quantum pattern recognition on real quantum processing units
Das, Sreetama
Zhang, Jingfu
Martina, Stefano
Suter, Dieter
Caruso, Filippo
QUANTUM MACHINE INTELLIGENCE, 2023, 5 (01)
[34] Quantum pattern recognition on real quantum processing units
Sreetama Das
Jingfu Zhang
Stefano Martina
Dieter Suter
Filippo Caruso
Quantum Machine Intelligence, 2023, 5
[35] Large-Scale Simulation of Quantum Computational Chemistry on a New Sunway Supercomputer
Shang, Honghui
Shen, Li
Fan, Yi
Xu, Zhiqian
Guo, Chu
Liu, Jie
Zhou, Wenhao
Ma, Huan
Lin, Rongfen
Yang, Yuling
Li, Fang
Wang, Zhuoya
Zhang, Yunquan
Li, Zhenyu
SC22: INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS, 2022,
[36] Resource-demand Estimation for Edge Tensor Processing Units
Herzog, Benedict
Reif, Stefan
Hemp, Judith
Hoenig, Timo
Schroeder-Preikschat, Wolfgang
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2022, 21 (05)
[37] Reliability of Google's Tensor Processing Units for Embedded Applications
Rech Junior, Rubens Luiz
Rech, Paolo
PROCEEDINGS OF THE 2022 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2022), 2022, : 376 - 381
[38] ELECTRONIC DATA PROCESSING IN CHEMISTRY - QUANTUM CHEMISTRY AND COMPUTERS
RITSCHL, F
ZULICKE, L
ALTENBUR.K
ZEITSCHRIFT FUR CHEMIE, 1971, 11 (08): : 281 - &
[39] Tensor product approximation with optimal rank in quantum chemistry
Chinnamsetty, Sambasiva Rao
Espig, Mike
Khoromskij, Boris N.
Hackbusch, Wolfgang
Flad, Heinz-Juergen
JOURNAL OF CHEMICAL PHYSICS, 2007, 127 (08):
[40] KERNEL COMPUTATIONS FROM LARGE-SCALE RANDOM FEATURES OBTAINED BY OPTICAL PROCESSING UNITS
Ohana, Ruben
Wacker, Jonas
Dong, Jonathan
Marmin, Sebastien
Krzakala, Florent
Filippone, Maurizio
Daudet, Laurent
2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2020, : 9294 - 9298

← 1 2 3 4 5 →