Computational modeling and simulation have become indispensable scientific tools in virtually all areas of chemical, biomolecular, and materials systems research. Computation can provide unique and detailed atomic level information that is difficult or impossible to obtain through analytical theories and experimental investigations. In addition, recent advances in micro-electronics have resulted in computer architectures with unprecedented computational capabilities, from the largest supercomputers to common desktop computers. Combined with the development of new computational domain science methodologies and novel programming models and techniques, this has resulted in modeling and simulation resources capable of providing results at or better than experimental chemical accuracy and for systems in increasingly realistic chemical environments.
The computational chemistry application software development community has a long history of adapting to the evolution of advanced computer architectures and technologies and creating efficient implementations of existing and newly proposed methodologies for the computer systems of the time. Sometimes, disruptive transformations in computer architectures, such as the advent of the vector machines in the 1980s, the parallel and massively parallel systems starting in the 1990s, and accelerated architectures followed by hybrid and heterogeneous architectures in the past decade, required a significant redesign of the algorithms and their implementation. The current rapid development of artificial intelligence approaches and the anticipated power that quantum computing may provide in the future will bring new challenges in methodology and software development.
Most recently, developers have prepared their codes for exascale computing resources by participating in application readiness programs, such as those at large user facilities,1 and by taking advantage of large scale development programs, such as the Exascale Computing Project of the Office of Science in the U.S. Department of Energy2,3 and the HANAMI project across both the EU and Japan. In this Special Topic issue on High Performance Computing in Chemical Physics, invited and contributed articles highlight some of these recent developments in computational chemistry to take advantage of the combination of the unprecedented power of computer systems available today for open science and the development of new methodologies and their implementations.
This Special Topic issue on High Performance Computing in Chemical Physics includes contributions covering a wide range of approaches to enable methodologies or entire applications to be used for chemical systems of ever-increasing size4 or in much reduced time-to-solution. These include novel ways to implement specific mathematical methods commonly used in computational chemistry,5 new implementations of chemical methods,6,7 and using fragmentation and iterative expansion methods to improve scalability.8–11
A common objective in many contributions is to improve performance for massively parallel and GPU-accelerated computing,12–16 including whole application suites of codes,17–21 multi-scale and multi-level models,22 and general frameworks and modules with optimization approaches.23–26
We thank all of the authors for the many wonderful contributions to this special issue. In addition, we thank the editorial staff who put in so much time to ensure the quality of this issue. T.L.W. and T.P.S. are supported by the Exascale Computing Project (Grant No. 17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. Part of the work (T.L.W.) was performed at Ames National Laboratory, which is operated for the U.S. Department of Energy by Iowa State University under Contract No. DE-AC02-07CH11358. Part of this work (T.P.S.) used resources of the Oak Ridge Leadership Computing Facility (OLCF) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. T.N. was supported by the Supercomputer Fugaku Project “System Enhancement and Exploration Category and System Maintenance and User Support Category” and “Program for Promoting Research on the Supercomputer Fugaku” (Realization of Innovative Light Energy Conversion Materials utilizing the Supercomputer Fugaku, Grant No. JPMXP1020210317), MEXT, Japan. This manuscript has been authored in part by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE). The U.S. government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
AUTHOR DECLARATIONS
Author Contributions
All the authors contributed equally to this work.
