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Physical Chemistry Chemical Physics

Utilizing high performance computing for chemistry: parallel computational chemistry

Wibe Albert de Jong, Eric J. Bylaska, Niranjan Govind, Curtis L. Janssen, Karol Kowalski, Thomas Müller, Ida M. B. Nielsen, Hubertus J. J. van Dam, Valera Veryazov, Roland H. Lindh

Published Jan 1, 2010• 102 citations
Publisher

Abstract

Parallel hardware has become readily available to the computational chemistry research community. This perspective will review the current state of parallel computational chemistry software utilizing high-performance parallel computing platforms. Hardware and software trends and their effect on quantum chemistry methodologies, algorithms, and software development will also be discussed.

DOI
10.1039/c002859b

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Parallel hardware has become readily available to the computational chemistry research community. This perspective will review the current state of parallel computational chemistry software utilizing high-performance parallel computing platforms. Hardware and software trends and their effect on quantum chemistry methodologies, algorithms, and software development will also be discussed.
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As the year-to-year gains in speeds of classical computers continue to taper off, computational chemists are increasingly examining quantum computing as a possible route to achieve greater computational performance. Quantum computers, built upon the properties of superposition, interference, and entanglement of quantum bits, offer, in principle, the possibility to outperform classical computers for solving many important classes of problems. In the field of chemistry, quantum algorithm development offers promising propositions for solving classically intractable problems in areas such as electronic structure, chemical quantum dynamics, spectroscopy, and cheminformatics. However, physical implementations of quantum computers are still in their infancy and have yet to outperform classical computers for useful computations. Still, quantum software development for chemistry is a highly active area of research. In this perspective, we summarize recent progress in the areas of quantum computing algorithms, hardware, and software, and we describe the challenges that remain for useful implementations of quantum computing for chemical applications.
Advances in computer hardware have pushed forward the size of chemical investigations that are accessible using quantum chemistry. However, because state-of-the-art quantum chemistry methods scale as N 5 - N7, the hardware advances can only take us so far. A key advance in the past decade has been the development of scalable (parallel) codes for highly correlated wavefunctions. Following a summary of the methods used in our approach to parallelism in GAMESS (General Atomic and Molecular Electronic Structure System), several applications that emphasize the efficiacy of scalable codes will be discussed. These include the prediction of potential new fuels, the study of new materials with desirable properties and the study of species of biological importance
The Massively Parallel Quantum Chemistry (MPQC) program is a 30-year-old project that enables facile development of electronic structure methods for molecules for efficient deployment to massively parallel computing architectures. Here, we describe the historical evolution of MPQC's design into its latest (fourth) version, the capabilities and modular architecture of today's MPQC, and how MPQC facilitates rapid composition of new methods as well as its state-of-the-art performance on a variety of commodity and high-end distributed-memory computer platforms.
Within the last decade much progress has been made in the experimental realization of quantum computing hardware based on a variety of physical systems. Rapid progress has been fuelled by the conviction that sufficiently powerful quantum machines will herald enormous computational advantages in many fields, including chemical research. A quantum computer capable of simulating the electronic structures of complex molecules would be a game changer for the design of new drugs and materials. Given the potential implications of this technology, there is a need within the chemistry community to keep abreast with the latest developments as well as becoming involved in experimentation with quantum prototypes. To facilitate this, here we review the types of quantum computing hardware that have been made available to the public through cloud services. We focus on three architectures, namely superconductors, trapped ions and semiconductors. For each one we summarize the basic physical operations, requirements and performance. We discuss to what extent each system has been used for molecular chemistry problems and highlight the most pressing hardware issues to be solved for a chemistry-relevant quantum advantage to eventually emerge.