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Semiempirical Quantum Chemical Calculations Accelerated on a Hybrid Multicore CPU-GPU Computing Platform

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons59126

Wu,  Xin
Research Department Thiel, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons58716

Koslowski,  Axel
Research Department Thiel, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons59045

Thiel,  Walter
Research Department Thiel, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

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Citation

Wu, X., Koslowski, A., & Thiel, W. (2012). Semiempirical Quantum Chemical Calculations Accelerated on a Hybrid Multicore CPU-GPU Computing Platform. Journal of Chemical Theory and Computation, 8(7), 2272-2281. doi:10.1021/ct3001798.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000E-E6B1-1
Abstract
In this work, we demonstrate that semiempirical quantum chemical calculations can be accelerated significantly by leveraging the graphics processing unit (GPU) as a coprocessor on a hybrid multicore CPU–GPU computing platform. Semiempirical calculations using the MNDO, AM1, PM3, OM1, OM2, and OM3 model Hamiltonians were systematically profiled for three types of test systems (fullerenes, water clusters, and solvated crambin) to identify the most time-consuming sections of the code. The corresponding routines were ported to the GPU and optimized employing both existing library functions and a GPU kernel that carries out a sequence of noniterative Jacobi transformations during pseudodiagonalization. The overall computation times for single-point energy calculations and geometry optimizations of large molecules were reduced by one order of magnitude for all methods, as compared to runs on a single CPU core.