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Using GPUs to compute fast Fourier transforms for crystal structure solution and refinement

JOURNAL OF APPLIED CRYSTALLOGRAPHY 2013年第3期46卷 594-600页

作者： Shalaby, ElSayed Mohamed Oliveira, Miguel Afonso Univ Coimbra Fac Ciencias & Tecnol Dept Fis Lab Instrumentacao & Fis Expt Particulas P-3004516 Coimbra Portugal

In the past few years, new hardware tools have become available for computing using the graphical processing units (GPUs) present in modern graphics cards. These GPUs allow efficient parallel calculations with a much higher throughput than microprocessors. In this work, fast Fourier transformation calculations used in SIR2011 software algorithms have been carried out using the power of the GPU, and the speed of the calculations has been compared with that achieved using normal CPUs.

关键词： crystal structure determination difference Fourier synthesis graphical processing units

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PyNX: high-performance computing toolkit for coherent X-ray imaging based on operators

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JOURNAL OF APPLIED CRYSTALLOGRAPHY 2020年第5期53卷 1404-1413页

作者： Favre-Nicolin, Vincent Girard, Gaetan Leake, Steven Carnis, Jerome Chushkin, Yuriy Kieffer, Jerome Paleo, Pierre Richard, Marie-Ingrid European Synchrotron ESRF 71 Ave Martyrs F-38000 Grenoble France Univ Grenoble Alpes Grenoble France CEA IRIG MEM Nanostruct & Synchrotron Radiat Lab F-38000 Grenoble France DESY D-22607 Hamburg Germany

The open-source PyNX toolkit has been extended to provide tools for coherent X-ray imaging data analysis and simulation. All calculations can be executed on graphical processing units (GPUs) to achieve high-performance computing speeds. The toolkit can be used for coherent diffraction imaging (CDI), ptychography and wavefront propagation, in the far- or near-field regime. Moreover, all imaging operations (propagation, projections, algorithm cycles...) can be implemented in Python as simple mathematical operators, an approach which can be used to easily combine basic algorithms in a tailored chain. Calculations can also be distributed to multiple GPUs, e.g. for large ptychography data sets. Command-line scripts are available for on-line CDI and ptychography analysis, either from raw beamline data sets or using the coherent X-ray imaging data format.

关键词： coherent X-ray imaging ptychography coherent diffraction imaging graphical processing units

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PARALLEL EFFICIENT METHOD OF MOMENTS EXPLOITING GRAPHICS processing units

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MICROWAVE AND OPTICAL TECHNOLOGY LETTERS 2010年第11期52卷 2568-2572页

作者： De Donno, D. Esposito, A. Monti, G. Tarricone, L. Univ Salento Dept Innovat Engn I-73100 Lecce Italy

In this article we adopt the graphical processing units as a low-cost and efficient solution of challenging electromagnetic numerical problems. Based on the compute unified device architecture, an optimized method of moments algorithm has been implemented which adopts direct solvers based on LU decomposition. Numerical results obtained on the practical case of a patch antenna analysis demonstrate the high performance of the approach. (C) 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52:2568-2572, 2010: View this article online at ***. DOI 10.1002/mop.25534

关键词： parallel computing method of moments mixed potential integral equations graphical processing units compute unified device architecture

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Accelerated computational micromechanics and its application to polydomain liquid crystal elastomers

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JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS 2021年 153卷

作者： Zhou, Hao Bhattacharya, Kaushik CALTECH Div Engn & Appl Sci Pasadena CA 91125 USA

We present an approach to solving problems in computational micromechanics that is amenable to massively parallel calculations through the use of graphical processing units (GPUs) and other accelerators. We apply it to study microstructure evolution in polydomain liquid crystal elastomers (LCEs). LCEs are rubber-like solids where rod-like nematic molecules are incorporated into the main or a side polymer chain. They undergo isotropic to nematic phase transition accompanied by spontaneous deformation which can be exploited for actuation. Further, they display a soft behavior at low temperatures due to the reorientation of the nematic directors. The problem of understanding nematic reorientation in the presence of realistic defects (non ideality) is computationally expensive, and we address this by efficiently exploiting GPUs. The approach is broadly applicable to various phenomena including crystal plasticity and phase transitions that are described by internal variable theories. We verify the approach against previous calculations and establish its performance by studying long wavelength instability of finite elasticity. Our numerical studies of LCEs provide insights into the director distribution and reorientation in polydomain specimens, and how these lead to soft behavior under multiaxial loading. The results show good agreement with experimental observations.

关键词： Micromechanics Liquid crystal elastomers Internal variable theories graphical processing units

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COMPARATIVE ANALYSIS OF 3D RTM IMPLEMENTATION STRATEGIES FOR AN EFFICIENT USE OF MEMORY IN A SINGLE GPU

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CT&F-CIENCIA TECNOLOGIA Y FUTURO 2018年第2期8卷 75-82页

作者： Salamanca, William-A Ramirez, Ana-B Vivas, Flor-A Univ Ind Santander Carrera 27 Calle 9 Bucaramanga 680002 Colombia Ecopetrol Inst Colombiano Petr Km 7 Via Bucaramanga Piedecuesta Piedecuesta 681011 Colombia

Reverse-Time Migration (RTM) is a two-way wave-equation based method used to generate images of the Earth's subsurface. RTM has been successfully used in seismic imaging as it allows defining complex structural areas. However, RTM is a highly computational expensive algorithm that requires the computation of both the source and the receiver wavefields for each shot. Fortunately, numerical methods that compute the wave propagation using the wave equation are highly parallelizable, so they can take leverage on GPU features. However, the main problem of a GPU-RTM implementation is memory management. To take advantage of the GPU computing capabilities, the transfers to host RAM memory storage, or more expensive hard disk storage must be avoided. We present the analysis of three different strategies to implement RTM using only the memory available on a single GPU: (1) Stored wavefield checkpointing (2) Backpropagation of source wavefield using stored boundaries, and (3) Backpropagation of source wavefield using the two last snapshots and random boundaries, showing that the large amount of memory required in the first two strategies becomes a restriction over the model size. The last method (using random boundary conditions) is shown as a suggested solution to the memory problem of using a single GPU.

关键词： graphical processing units Reverse-Time Migration 3D Wavefield Computation Strategies

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

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JOURNAL OF COMPUTATIONAL CHEMISTRY 2015年第18期36卷 1399-1409页

作者： Fernandes, Kyle D. Renison, C. Alicia Naidoo, Kevin J. Univ Cape Town Sci Comp Res Unit ZA-7701 Rondebosch South Africa Univ Cape Town Dept Chem ZA-7701 Rondebosch South Africa

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. (c) 2015 Wiley Periodicals, Inc.

关键词： Hartree-Fock quantum supercharger library graphical processing units parallel computing accelerator hardware Fock matrix

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Parallel interior-point solver for block-structured nonlinear programs on SIMD/GPU architectures

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OPTIMIZATION METHODS & SOFTWARE 2024年第4期39卷 874-897页

作者： Pacaud, Francois Schanen, Michel Shin, Sungho Maldonado, Daniel Adrian Anitescu, Mihai Mines Paris PSL Ctr Automat & Syst Paris France Argonne Natl Lab Math & Comp Sci Dept Lemont IL USA 60 Blvd St Michel F-75006 Paris France

We investigate how to port the standard interior-point method to new exascale architectures for block-structured nonlinear programs with state equations. Computationally, we decompose the interior-point algorithm into two successive operations: the evaluation of the derivatives and the solution of the associated Karush-Kuhn-Tucker (KKT) linear system. Our method accelerates both operations using two levels of parallelism. First, we distribute the computations on multiple processes using coarse parallelism. Second, each process uses SIMD/GPU accelerators locally to accelerate the operations using fine-grained parallelism. The KKT system is reduced by eliminating the inequalities and the state variables from the corresponding equations. We demonstrate our method's capability on the supercomputer Polaris, a testbed for the future exascale Aurora system. Each node is equipped with four GPUs, a setup amenable to our two-level approach. Our experiments on the stochastic optimal power flow problem show that the reduction method is 50x faster than the sparse linear solver HSL MA57 running in serial on the CPU, and 6x faster than Pardiso running in parallel on CPU on the same number of processes.

关键词： Nonlinear programming interior-point method distributed optimization multiprocessing graphical processing units

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Quantum supercharger library: Hyper-parallel integral derivatives algorithms for ab initio QM/MM dynamics

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JOURNAL OF COMPUTATIONAL CHEMISTRY 2015年第18期36卷 1410-1419页

作者： Renison, C. Alicia Fernandes, Kyle D. Naidoo, Kevin J. Univ Cape Town Sci Comp Res Unit ZA-7701 Cape Town South Africa Univ Cape Town Dept Chem ZA-7701 Cape Town South Africa

This article describes an extension of the quantum supercharger library (QSL) to perform quantum mechanical (QM) gradient and optimization calculations as well as hybrid QM and molecular mechanical (QM/MM) molecular dynamics simulations. The integral derivatives are, after the two-electron integrals, the most computationally expensive part of the aforementioned calculations/simulations. Algorithms are presented for accelerating the one- and two-electron integral derivatives on a graphical processing unit (GPU). It is shown that a Hartree-Fock ab initio gradient calculation is up to 9.3X faster on a single GPU compared with a single central processing unit running an optimized serial version of GAMESS-UK, which uses the efficient Schlegel method for s- and l-orbitals. Benchmark QM and QM/MM molecular dynamics simulations are performed on cellobiose in vacuo and in a 39 angstrom water sphere (45 QM atoms and 24843 point charges, respectively) using the 6-31G basis set. The QSL can perform 9.7 ps/day of ab initio QM dynamics and 6.4 ps/day of QM/MM dynamics on a single GPU in full double precision. (c) 2015 Wiley Periodicals, Inc.

关键词： integral derivatives graphical processing units ionic force Pulay force code acceleration GPU GAMESS-UK quantum supercharger library QSL QM MM

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Simplified graphical Processor Acceleration of the Standard and High-Order Finite-Difference Time-Domain Algorithms

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ELECTROMAGNETICS 2012年第7期32卷 401-410页

作者： Hadi, Mohammed F. Kuwait Univ Dept Elect Engn Safat 13060 Kuwait

A computationally efficient and streamlined approach for coding a high order finite-difference time-domain algorithm on both central and graphical processing units is presented. This objective was achieved through extending the update equations of the convolutional perfectly-matched layer absorbing boundary conditions throughout the numerical domain with appropriate parameter selections. It is demonstrated that the resulting appreciable increase in the floating-point operations count would result in only an egligible loss of overall computational efficiency using either central processing units or graphical processing units. This achievement translates into sizable reductions in code complexity and development costs. Comparative analyses were also presented for the standard finite-difference time-domain method, resulting in an efficient accelerated algorithm that does not degrade with model size reduction.

关键词： finite-difference time-domain method graphical processing units perfectly-matched layer absorbing boundary conditions high-order methods

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Multi-GPU 3D k-nearest neighbors computation with application to ICP, point cloud smoothing and normals computation

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PARALLEL COMPUTING 2024年 121卷

作者： Agathos, Alexander Azariadis, Philip Univ Aegean Konstantinoupoleos 1 Syros 84100 Greece Univ West Attica P Ralli & Thivon 250 Athens 12244 Greece

The k-Nearest Neighbors algorithm is a fundamental algorithm that finds applications in many fields like Machine Learning, Computer Graphics, Computer Vision, and others. The algorithm determines the closest points (d-dimensional) of a reference set R according to a query set of points Q under a specific metric (Euclidean, Mahalanobis, Manhattan, etc.). This work focuses on the utilization of multiple graphical processing units for the acceleration of the k-Nearest Neighbors algorithm with large or very large sets of 3D points. With the proposed approach the space of the reference set is divided into a 3D grid which is used to facilitate the search for the nearest neighbors. The search in the grid is performed in a multiresolution manner starting from a high-resolution grid and ending up in a coarse one, thus accounting for point clouds that may have non-uniform sampling and/or outliers. Three important algorithms in reverse engineering are revisited and new multi-GPU versions are proposed based on the introduced KNN algorithm. More specifically, the new multi-GPU approach is applied to the Iterative Closest Point algorithm, to the point cloud smoothing, and to the point cloud normal vectors computation and orientation problem. A series of tests and experiments have been conducted and discussed in the paper showing the merits of the proposed multi-GPU approach.

关键词： k-nearest neighbors algorithm Parallel processing graphical processing units Iterative Closest Point algorithm Point cloud smoothing Point cloud normal vectors computation

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