Harnessing the power of graphics processing units to accelerate computational chemistry
Electron Repulsion Integral (ERI) and its derivative evaluation is the limiting factor for selfconsistentfield (SCF) and Density Functional Theory (DFT) calculations. Therefore, calculation of these quantities on graphical processing Units (GPUs) can significantly accelerate quantum chemical calculations. Recurrence relations, one of the fastest ERI evaluation algorithms currently available, are used to compute ERIs. A directSCF scheme to assemble the Fock matrix and gradient efficiently is presented, wherein ERIs are evaluated onthefly to avoid CPUGPU data transfer, a well known architectural bottleneck in GPU specific computation. A machinegenerated code is utilized to calculate different ERI types efficiently. However, only s, p and d ERIs and s, p derivatives can be executed on GPUs using the current version of CUDA and NVidia GPUs. Hence, we developed an algorithm to compute f type ERIs and d type ERI derivatives on GPUs. Our benchmarks shows the performance GPU enable ERI and ERI derivative computation yielded speedups of 10~100 times relative to traditional CPU execution. An accuracy analysis using doubleprecision calculations demonstrates the accuracy is satisfactory for most applications. Besides ab inito quantum chemistry methods, GPU programming can be applied to a number of computational chemistry applications, for example, The Weighted Histogram Analysis Method (WHAM), a technique to compute potentials of mean force. We present an implementation of multidimensional WHAM on Graphical Processing Units (GPUs), which significantly accelerates its computational performance. Our test cases, that simulate twodimensional free energy surfaces, yielded speedups up to 1000 times in double precision. Moreover, speedups of 2100 times can be achieved when single precision is used whose use introduces errors of less than 0.2 kcal/mol. These applications of GPU computing in computational chemistry can significantly benefit the whole computational chemistry community.
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Electronic Theses & Dissertations
 Copyright Status
 In Copyright
 Material Type

Theses
 Authors

Miao, Yipu
 Thesis Advisors

Merz, Kenneth M.
 Committee Members

Aktulga, Metin
Colbry, Dirk
Hunt, Katharine
 Date
 2015
 Program of Study

Chemistry  Doctor of Philosophy
 Degree Level

Doctoral
 Language

English
 Pages
 xvii, 153 pages
 ISBN

9781321598520
1321598521
 Permalink
 https://doi.org/doi:10.25335/M5S39N