Bridges-2 Webinar Series
Presenting topics to enable the Bridges-2 user community to optimize and accelerate their research
High performance GPU accelerated MuST software
April 19, 2023
1:00 pm – 2:00 pm Eastern time
Join us for this webinar describing how to accelerate electronic structure calculations in the MuST software using multiple GPUs on Bridges-2.
Dr. Xiao Liang, Pittsburgh Supercomputing Center
liangstein@psc.edu
Abstract
The MuST package is computational software designed for ab-initio electronic structure calculations for solids. The Locally Self-consistent Multiple Scattering (LSMS) method implemented in MuST allows one to perform the electronic structure calculation for systems with a large number of atoms per unit cell. For the LSMS method, the major computational challenge is the matrix inversion for the scattering matrix calculation, which could take more than 90% of the computing time. However, the matrix inversion can be significantly accelerated by modern graphical processing units (GPUs). In this presentation, Dr. Liang will discuss the team’s approach to code acceleration by offloading the matrix inverse tasks to the GPUs through a Fortran-C interface to the CUDA code. The team found that a high speedup ratio can be achieved by GPU acceleration. Dr. Liang will discuss specific source code and job script examples to show how they parallelize the computational tasks over multiple GPUs on Bridges-2. Finally they will report their performance results on the calculation of NiAu alloy, a candidate for thermoelectric material. This work was supported by the National Science Foundation through the OAC-21939536 Characteristic Science Applications for the Leadership Class Computing Facility award.
About Xiao Liang
Xiao Liang holds a Ph.D in Physics from the University of Science and Technology of China (USTC), and he has two postdoc experiences at Tsinghua University and USTC. He joined the Pittsburgh Supercomputing Center (PSC) in 2023 as a post-doctoral researcher working with Dr. Yang Wang (PSC) on NSF’s Leadership Class Computing Facility Characteristic Science Applications project to optimize the MuST software package for future leadership computing systems. His research interests include development of numerical methods and performance optimization for scientific applications, heterogeneous computing, and ab-initio calculation of quantum systems, as well as machine learning and quantum computing.