S
Sarom S. Leang
Researcher at Scripps Health
Publications - 10
Citations - 999
Sarom S. Leang is an academic researcher from Scripps Health. The author has contributed to research in topics: GAMESS & Density functional theory. The author has an hindex of 8, co-authored 9 publications receiving 566 citations. Previous affiliations of Sarom S. Leang include Iowa State University.
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Journal ArticleDOI
Recent developments in the general atomic and molecular electronic structure system.
Giuseppe M. J. Barca,Colleen Bertoni,Laura Carrington,Dipayan Datta,Nuwan De Silva,J. Emiliano Deustua,Dmitri G. Fedorov,Jeffrey R. Gour,Anastasia O. Gunina,Emilie B. Guidez,Taylor Harville,Stephan Irle,Joe Ivanic,Karol Kowalski,Sarom S. Leang,Hui Li,Wei Li,Jesse J. Lutz,Ilias Magoulas,Joani Mato,Vladimir Mironov,Hiroya Nakata,Buu Q. Pham,Piotr Piecuch,David Poole,Spencer R. Pruitt,Alistair P. Rendell,Luke Roskop,Klaus Ruedenberg,Tosaporn Sattasathuchana,Michael W. Schmidt,Jun Shen,Lyudmila V. Slipchenko,Masha Sosonkina,Vaibhav Sundriyal,Ananta Tiwari,Jorge L. Galvez Vallejo,Bryce Westheimer,Marta Włoch,Peng Xu,Federico Zahariev,Mark S. Gordon +41 more
TL;DR: 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, which include fragmentation methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory.
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Benchmarking the Performance of Time-Dependent Density Functional Methods
TL;DR: The global-hybrid version of the Perdew-Burke-Ernzerhoff GGA density functional (PBE0) is found to offer the best overall performance with a mean absolute error (MAE) of 0.28 eV, while the local density approximation functional (SVWN) outperformed all non-GH GGAs tested.
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Functional derivatives of meta-generalized gradient approximation (meta-GGA) type exchange-correlation density functionals
TL;DR: The TDDFT working equations for meta-GGA density functionals are presented here for the first time, together with the technical details of their computer implementation.
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Quantum Chemical Calculations Using Accelerators: Migrating Matrix Operations to the NVIDIA Kepler GPU and the Intel Xeon Phi
TL;DR: This paper considers how matrix operations in typical quantum chemical calculations can be migrated to the GPU and Phi systems, and finds the GPU outperforms the Phi for both square and nonsquare matrix multiplications.
Journal ArticleDOI
Energy-Efficient Computational Chemistry: Comparison of x86 and ARM Systems.
Kristopher Keipert,Gaurav Mitra,Vaibhav Sunriyal,Sarom S. Leang,Masha Sosonkina,Alistair P. Rendell,Mark S. Gordon +6 more
TL;DR: The computational efficiency and energy-to-solution of several applications using the GAMESS quantum chemistry suite of codes is evaluated for 32-bit and 64-bit ARM-based computers, and compared to an x86 machine.