Publications by authors named "Jorge Galvez Vallejo"

The primary focus of GAMESS over the last 5 years has been the development of new high-performance codes that are able to take effective and efficient advantage of the most advanced computer architectures, both CPU and accelerators. These efforts include employing density fitting and fragmentation methods to reduce the high scaling of well-correlated (e.g.

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The bonding structures of tetrahedrane, phosphatetrahedrane, diphosphatetrahedrane and triphosphatetrahedrane are studied by employing an intrinsic quasi-atomic orbital analysis. Ethane, cyclopropane and tetrahedral P are employed as reference systems. The orbital analysis is paired with the computation of strain energies isodesmic reactions.

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Electronic structure calculations have the potential to predict key matter transformations for applications of strategic technological importance, from drug discovery to material science and catalysis. However, a predictive physicochemical characterization of these processes often requires accurate quantum chemical modeling of complex molecular systems with hundreds to thousands of atoms. Due to the computationally demanding nature of electronic structure calculations and the complexity of modern high-performance computing hardware, quantum chemistry software has historically failed to operate at such large molecular scales with accuracy and speed that are useful in practice.

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An quantum chemical approach for the modeling of propellant degradation is presented. Using state-of-the-art bonding analysis techniques and composite methods, a series of potential degradation reactions are devised for a sample hydroxyl-terminated-polybutadiene (HTPB) type solid fuel. By applying thermochemical procedures and isodesmic reactions, accurate thermochemical quantities are obtained using a modified G3 composite method based on the resolution of the identity.

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In recent years, parallelism via multithreading has become extremely important to the optimization of high-performance electronic structure theory codes. Such multithreading is generally achieved via OpenMP constructs, using a fork-join threading model to enable thread-level data parallelism within the code. An alternative approach to multithreading is , which displays multiple benefits relative to fork-join thread parallelism.

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A novel implementation of the self-consistent field (SCF) procedure specifically designed for high-performance execution on multiple graphics processing units (GPUs) is presented. The algorithm offloads to GPUs the three major computational stages of the SCF, namely, the calculation of one-electron integrals, the calculation and digestion of electron repulsion integrals, and the diagonalization of the Fock matrix, including SCF acceleration via DIIS. Performance results for a variety of test molecules and basis sets show remarkable speedups with respect to the state-of-the-art parallel GAMESS CPU code and relative to other widely used GPU codes for both single and multi-GPU execution.

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The quasi-atomic orbital (QUAO) bonding analysis introduced by Ruedenberg and co-workers is used to develop an understanding of the hydrogen bonds in small water clusters, from the dimer through the hexamer (bag, boat, book, cyclic, prism and cage conformers). Using kinetic bond orders as a metric, it is demonstrated that as the number of waters in simple cyclic clusters increases, the hydrogen bonds strengthen, from the dimer through the cyclic hexamer. However, for the more complex hexamer isomers, the strength of the hydrogen bonds varies, depending on whether the cluster contains double acceptors and/or double donors.

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We present a high-performance, GPU (graphics processing unit)-accelerated algorithm for building the Fock matrix. The algorithm is designed for efficient calculations on large molecular systems and uses a novel dynamic load balancing scheme that maximizes the GPU throughput and avoids thread divergence that could occur due to integral screening. Additionally, the code adopts a novel ERI digestion algorithm that exploits all forms of permutational symmetry, combines efficiently the evaluation of both Coulomb and exchange terms together, and eliminates explicit thread synchronization requirements.

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In the field of electronic structure theory, many optimizations, ranging from accelerator offloading to exploitation of modern programming constructs, have been used to improve the performance of quantum chemistry software. However, one area that has remained largely unexplored is the space of novel programming languages that can provide unique benefits to quantum chemistry software development. One such programming language is Julia, an interpreted language designed to achieve the performance of high-performance, statically compiled languages.

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Electronic structure theory (especially quantum chemistry) has thrived and has become increasingly relevant to a broad spectrum of scientific endeavors as the sophistication of both computer architectures and software engineering has advanced. This article provides a brief history of advances in both hardware and software, from the early days of IBM mainframes to the current emphasis on accelerators and modern programming practices.

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A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory.

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