Acceleration of the GAMESS‐UK electronic structure package on graphical processing units

Wilkinson, Karl A.; Sherwood, Paul; Guest, Martyn F.; Naidoo, Kevin J.

doi:10.1002/jcc.21815

Cited by 45 publications

(45 citation statements)

References 13 publications

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“…Computing multiple electronic structures for chemical models that are in excess of hundreds of atoms is often out of reach for most midlevel computer hardware systems. This has inspired us and others to rewrite the basic algorithms responsible for the compute bottlenecks in HF calculations to take advantage of compute accelerators such as Graphical Processing Units (GPUs) …”

Section: Introductionmentioning

confidence: 99%

Quantum supercharger library: Hyper-parallelism of the Hartree-Fock method

2015

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We present here a set of algorithms that completely rewrites the Hartree-Fock (HF) computations common to many legacy electronic structure packages (such as GAMESS-US, GAMESS-UK, and NWChem) into a massively parallel compute scheme that takes advantage of hardware accelerators such as Graphical Processing Units (GPUs). The HF compute algorithm is core to a library of routines that we name the Quantum Supercharger Library (QSL). We briefly evaluate the QSL's performance and report that it accelerates a HF 6-31G Self-Consistent Field (SCF) computation by up to 20 times for medium sized molecules (such as a buckyball) when compared with mature Central Processing Unit algorithms available in the legacy codes in regular use by researchers. It achieves this acceleration by massive parallelization of the one- and two-electron integrals and optimization of the SCF and Direct Inversion in the Iterative Subspace routines through the use of GPU linear algebra libraries. © 2015 Wiley Periodicals, Inc.

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Section: Introductionmentioning

confidence: 99%

Quantum supercharger library: Hyper-parallelism of the Hartree-Fock method

2015

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“…Since 2008, GPUs have been used in two-electron integral computations, [1][2][3][4][5][6][7] the Hartree2Fock (HF) method, [8][9][10][11][12] density functional theory (DFT), [13][14][15][16][17][18] second-order Møller2Plesset perturbation (MP2) theory, [19,20] coupled cluster theory, [21][22][23][24][25] and the semiempirical method. Since 2008, GPUs have been used in two-electron integral computations, [1][2][3][4][5][6][7] the Hartree2Fock (HF) method, [8][9][10][11][12] density functional theory (DFT), [13][14][15][16][17][18] second-order Møller2Plesset perturbation (MP2) theory, [19,20] coupled cluster theory, [21][22][23]…”

Section: Introductionmentioning

confidence: 99%

Linear‐scaling self‐consistent field calculations based on divide‐and‐conquer method using resolution‐of‐identity approximation on graphical processing units

Yoshikawa

Nakai

2014

J Comput Chem

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Graphical processing units (GPUs) are emerging in computational chemistry to include Hartree-Fock (HF) methods and electron-correlation theories. However, ab initio calculations of large molecules face technical difficulties such as slow memory access between central processing unit and GPU and other shortfalls of GPU memory. The divide-and-conquer (DC) method, which is a linear-scaling scheme that divides a total system into several fragments, could avoid these bottlenecks by separately solving local equations in individual fragments. In addition, the resolution-of-the-identity (RI) approximation enables an effective reduction in computational cost with respect to the GPU memory. The present study implemented the DC-RI-HF code on GPUs using math libraries, which guarantee compatibility with future development of the GPU architecture. Numerical applications confirmed that the present code using GPUs significantly accelerated the HF calculations while maintaining accuracy.

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“…During the past years, theoretical chemistry softwares have been modified or developed from scratch to benefit from the massively parallel GPU technology. [8, 12–24] The Vienna Ab initio Simulation Package (VASP) is an efficient plane‐wave code based on periodic DFT. [25–28] It allows theoretical study of chemical systems via energy and forces calculations, which permit geometry optimizations, molecular dynamics simulations, and determination of a wide range of physicochemical properties for solids or surfaces.…”

Section: Introductionmentioning

confidence: 99%

Accelerating VASP electronic structure calculations using graphic processing units

et al. 2012

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We present a way to improve the performance of the electronic structure Vienna Ab initio Simulation Package (VASP) program. We show that high-performance computers equipped with graphics processing units (GPUs) as accelerators may reduce drastically the computation time when offloading these sections to the graphic chips. The procedure consists of (i) profiling the performance of the code to isolate the time-consuming parts, (ii) rewriting these so that the algorithms become better-suited for the chosen graphic accelerator, and (iii) optimizing memory traffic between the host computer and the GPU accelerator. We chose to accelerate VASP with NVIDIA GPU using CUDA. We compare the GPU and original versions of VASP by evaluating the Davidson and RMM-DIIS algorithms on chemical systems of up to 1100 atoms. In these tests, the total time is reduced by a factor between 3 and 8 when running on n (CPU core + GPU) compared to n CPU cores only, without any accuracy loss.

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Acceleration of the GAMESS‐UK electronic structure package on graphical processing units

Cited by 45 publications

References 13 publications

Quantum supercharger library: Hyper-parallelism of the Hartree-Fock method

Quantum supercharger library: Hyper-parallelism of the Hartree-Fock method

Linear‐scaling self‐consistent field calculations based on divide‐and‐conquer method using resolution‐of‐identity approximation on graphical processing units

Accelerating VASP electronic structure calculations using graphic processing units

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