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Andrey Asadchev
This document covers the basics of computational chemistry and how using the modern programming techniques the theory can be efficiently implemented on digital computers. The computer implementations are developed from the core two-electron integrals to many-body and coupled cluster algorithms. A particular attention is paid to the physical constraints of he computer resources and the […]
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Robin M. Betz, Ross C. Walker
Continuous integration is the software engineering principle of rapid and automated development and testing. We identify several key points of continuous integration and demonstrate how they relate to the needs of computational science projects by discussing the implementation and relevance of these principles to AMBER, a large and widely used molecular dynamics software package. The […]
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Vlad Slavici
The clock speed of current CPUs and RAM has stopped scaling with Moore’s Law. Yet the scale of applications in science and engineering continues to increase. In order to address this scaling of applications, newer NUMA architectures are emerging. These include parallel disks, hybrid CPU-GPU, and many-core CPUs. Existing CPU-based algorithms, as well as legacy […]
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Vlad Slavici, Raghu Varier, Gene Cooperman, Robert J. Harrison
Graphics Processing Units (GPUs) are becoming the workhorse of scalable computations. MADNESS is a scientific framework used especially for computational chemistry. Most MADNESS applications use operators that involve many small tensor computations, resulting in a less regular organization of computations on GPUs. A single GPU kernel may have to multiply by hundreds of small square […]
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Istvan Lorentz, Razvan Andonie, Levente Fabry-Asztalos
We focus on the following computational chemistry problem: Given a subset of the exact distances between atoms, reconstruct the three-dimensional position of each atom in the given molecule. The distance matrix is generally sparse. This problem is both important and challenging. Our contribution is a novel combination of two known techniques (parallel breadth-first search and […]
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Yuki Furukawa, Ryota Koga, Koji Yasuda
Computational quantum chemistry mehods such as the Hartree-Fock (HF), the density functional theory (DFT) or the fragment molecular orbital (FMO) require heavy computational resources. In this study they are accelerated by using graphics processing units (GPUs) and the vector instruction set (AVX) of latest CPU. PRISM algorithm to evaluate the electron repulsion integrals was vectorized […]
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Long Wang, Weile Jia, Xuebin Chi, Yue Wu, Weiguo Gao, Lin-Wang Wang
In this work, we present our implementation of the density functional theory (DFT) plane wave pseudopotential (PWP) calculations on GPU clusters. This GPU version is developed based on a CPU DFT-PWP code: PEtot, which can calculate up to a thousand atoms on thousands of processors. Our test indicates that the GPU version can have a […]
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A. Eugene DePrince III, Jeff R. Hammond, Stephen K. Gray
Heterogeneous nodes composed of a multicore CPU and at least one graphics processing unit (GPU) are increasingly common in high-performance scientific computing, and significant programming effort is currently being undertaken to port existing scientific algorithms to these unique architectures. We present implementations for two many-body quantum chemistry methods on heterogeneous nodes: the coupled-cluster with single […]
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Maxwell Hutchinson, Michael Widom
General purpose graphical processing units (GPU’s) offer high processing speeds for certain classes of highly parallelizable computations, such as matrix operations and Fourier transforms, that lie at the heart of first-principles electronic structure calculations. Inclusion of exact-exchange increases the cost of density functional theory by orders of magnitude, motivating the use of GPU’s. Porting the […]
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A. Eugene DePrince, Jeff R. Hammond
he iterative solution of the coupled-cluster with single and double excitations (CCSD) equations is a very time-consuming component of the "gold standard" in quantum chemistry, the CCSD(T) method. In an effort to accelerate accurate quantum mechanical calculations, we explore two implementation strategies for the iterative solution of the CC equations on graphics procesing units (GPUs). […]
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Urban Borstnik, Benjamin T. Miller, Bernard R. Brooks, Dusanka Janezic
Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition […]
Narayan Ganesan, Brad A. Bauer, Timothy R. Lucas, Sandeep Patel, Michela Taufer
We present results of molecular dynamics simulations of fully hydrated DMPC bilayers performed on graphics processing units (GPUs) using current state-of-the-art non-polarizable force fields and a local GPU-enabled molecular dynamics code named FEN ZI. We treat the conditionally convergent electrostatic interaction energy exactly using the particle mesh Ewald method (PME) for solution of Poisson’s Equation […]
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