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The Advanced Concepts in Electronic Structure (ACES) III software is a completely rewritten implementation for parallel computer architectures of the most used capabilities in ACES II, including the calculation of the electronic structure of molecular ground states and excited states, and determination of molecular geometries and of vibrational frequencies using many‐body and coupled cluster methods. To achieve good performance on modern parallel systems while simultaneously offering a software development environment that allows rapid implementation of new methods and algorithms, ACES III was written using a new software infrastructure, the super instruction architecture comprising a domain‐specific language, super instruction assembly language (SIAL), and a sophisticated runtime environment, super instruction processor (SIP). The architecture of ACES III is described as well as the inner workings of SIAL and SIP. The execution performance of ACES III and the productivity of programming in SIAL are discussed. © 2011 John Wiley & Sons, Ltd. WIREs Comput Mol Sci 2011 1 895–901 DOI:10.1002/wcms.77This article is categorized under: Software > Quantum Chemistry

The concept of an information structure is introduced as a unifying principle behind several of the numerous algorithms that have been proposed for the distributed mutual exclusion problem. This approach allows the development of a generalized mutual exclusion algorithm that accepts a particular information structure at initialization and realizes both known and new algorithms as special cases. Two simple performance metrics of a realized algorithm can be obtained directly from the information structure. A new failure recovery mechanism called local recovery, which requires no coordination between nodes and no additional messages beyond that needed for failure detection, is introduced.

Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.

The advanced concepts in electronic structure (ACES) programs are products of the Bartlett research group at the University of Florida. They consist of ACES II, which is serial, and ACES III and Aces4, which are massively parallel. All three programs are publically available free of charge. The focus of the ACES implementations is coupled cluster theory and many-body-perturbation theory. We give an overview of the ACES programs, discuss the many features of the program systems, and document the number of benchmarks.