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Acceleration of split-field finite difference time-domain method for anisotropic media by means of graphics processing unit computing

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OPTICAL ENGINEERING 2014年第1期53卷 011005-011005页

作者： Frances, Jorge Bleda, Sergio Lazara Alvarez, Mariela Javier Martinez, Francisco Marquez, Andres Neipp, Cristian Belendez, Augusto Univ Alicante San Vicente del Raspeig Drive Dept Phys Syst Engn Alicante 3080 Spain Univ Alicante San Vicente del Raspeig Drive Univ Inst Phys Sci Alicante 3080 Spain

The implementation of split-field finite difference time domain (SF-FDTD) applied to light-wave propagation through periodic media with arbitrary anisotropy method in graphics processing units (GPUs) is described. The SF-FDTD technique and the periodic boundary condition allow the consideration of a single period of the structure reducing the simulation grid. Nevertheless, the analysis of the anisotropic media implies considering all the electromagnetic field components and the use of complex notation. These aspects reduce the computational efficiency of the numerical method compared with the isotropic and nonperiodic implementation. Specifically, the implementation of the SF-FDTD in the Kepler family of GPUs of NVIDIA is presented. An analysis of the performance of this implementation is done, and several applications have been considered in order to estimate the possibilities provided by both the formalism and the implementation into GPU: binary phase gratings and twisted-nematic liquid crystal cells. Regarding the analysis of binary phase gratings, the validity of the scalar diffraction theory is evaluated by the comparison of the diffraction efficiencies predicted by SF-FDTD. The analysis for the second order of diffraction is extended, which is considered as a reference for the transmittance obtained by the SF-FDTD scheme for periodic media. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： split-field finite difference time domain graphics processing unit computing anisotropic media diffraction efficiency polarization gratings binary phase gratings

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Evolution of the SLATE linear algebra library

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE computing APPLICATIONS 2025年第1期39卷 3-17页

作者： Gates, Mark Abdelfattah, Ahmad Akbudak, Kadir Al Farhan, Mohammed Alomairy, Rabab Bielich, Daniel Burgess, Treece Cayrols, Sebastien Lindquist, Neil Sukkari, Dalal YarKhan, Asim Univ Tennessee Innovat Comp Lab Suite 203 Claxton1122 Volunteer Blvd Knoxville TN 37996 USA King Abdullah Univ Sci & Technol KAUST ECRC Extreme Comp Res Ctr Thuwal Saudi Arabia Hewlett Packard Enterprise HPE Spring TX USA MIT 77 Massachusetts Ave Cambridge MA 02139 USA Ansys Canonsburg PA USA NVIDIA Santa Clara CA USA Oak Ridge Natl Lab Oak Ridge TN USA

SLATE (Software for Linear Algebra Targeting Exascale) is a distributed, dense linear algebra library targeting both CPU-only and GPU-accelerated systems, developed over the course of the Exascale computing Project (ECP). While it began with several documents setting out its initial design, significant design changes occurred throughout its development. In some cases, these were anticipated: an early version used a simple consistency flag that was later replaced with a full-featured consistency protocol. In other cases, performance limitations and software and hardware changes prompted a redesign. Sequential communication tasks were parallelized;host-to-host MPI calls were replaced with GPU device-to-device MPI calls;more advanced algorithms such as Communication Avoiding LU and the Random Butterfly Transform (RBT) were introduced. Early choices that turned out to be cumbersome, error prone, or inflexible have been replaced with simpler, more intuitive, or more flexible designs. Applications have been a driving force, prompting a lighter weight queue class, nonuniform tile sizes, and more flexible MPI process grids. Of paramount importance has been building a portable library that works across several different GPU architectures - AMD, Intel, and NVIDIA - while keeping a clean and maintainable codebase. Here we explore the evolving design choices and their effects, both in terms of performance and software sustainability.

关键词： High-performance computing graphics processing unit computing linear algebra

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graphics processing unit-enabled path planning based on global evolutionary dynamic programming and local genetic algorithm optimization

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APPLIED SOFT computing 2025年 176卷

作者： Ou, Junlin Song, Ge Wang, Yi Univ South Carolina Dept Mech Engn Columbia SC 29208 USA

This paper presents a novel path planning method for real-time robotic path planning in a dynamic environment involving moving obstacles. It combines on a holistic platform a global approach to rapidly generate initial paths of prominent diversity and a heuristic approach to enable local path refinement for enhanced computational efficiency, exploration, and robustness. The global approach innovates a formulation that treats a path planning problem with a visibility graph as a Markov decision process and decomposes the process into many subproblems. A new evolutionary dynamic programming approach (EDP) is proposed to solve these subproblems in an iterative manner using graphics processing unit (GPU) computing to allow backpropagation of state values from goal to start points. The EDP generates multiple feasible initial paths with salient state values, each initializing an independent genetic algorithm (GA) optimization on waypoints only near the mobile robot, and all GAs are run in parallel on GPU, further improving exploration and convergence speed. The strategy to fully utilize CPU/GPU resources for various components in the pipeline is also established. The proposed algorithms are then implemented on an edge computing device (Jetson AGX Xavier) onboard a mobile robot (TurtleBot 3 Waffle Pi). Optimal paths can be continuously generated at the rate of 0.1 seconds/path, enabling successful obstacle avoidance and robot navigation through dynamic environments and, hence, verifying the real-time capabilities and accuracy of the present method. Compared to other benchmarks, the present method greatly enhances path planning robustness, computing speed, and path quality.

关键词： Dynamic programming Genetic algorithm Markov decision process Path planning graphics processing unit computing

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Lattice Microbes: High-Performance Stochastic Simulation Method for the Reaction-Diffusion Master Equation

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JOURNAL OF COMPUTATIONAL CHEMISTRY 2013年第3期34卷 245-255页

作者： Roberts, Elijah Stone, John E. Luthey-Schulten, Zaida Univ Illinois Dept Chem Urbana IL 61801 USA Univ Illinois Ctr Phys Living Cells Urbana IL 61801 USA Univ Illinois Beckman Inst Urbana IL 61801 USA

Spatial stochastic simulation is a valuable technique for studying reactions in biological systems. With the availability of high-performance computing (HPC), the method is poised to allow integration of data from structural, single-molecule and biochemical studies into coherent computational models of cells. Here, we introduce the Lattice Microbes software package for simulating such cell models on HPC systems. The software performs either well-stirred or spatially resolved stochastic simulations with approximated cytoplasmic crowding in a fast and efficient manner. Our new algorithm efficiently samples the reaction-diffusion master equation using NVIDIA graphics processing units and is shown to be two orders of magnitude faster than exact sampling for large systems while maintaining an accuracy of similar to 0.1%. Display of cell models and animation of reaction trajectories involving millions of molecules is facilitated using a plug-in to the popular VMD visualization platform. The Lattice Microbes software is open source and available for download at http://***/schulten/lm (C) 2012 Wiley Periodicals, Inc. DOI: 10.1002/jcc.23130

关键词： chemical master equation reaction-diffusion master equation Gillespie algorithm stochastic simulation graphics processing unit computing

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Leveraging the accelerated processing units for seismic imaging: A performance and power efficiency comparison against CPUs and GPUs

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE computing APPLICATIONS 2018年第6期32卷 819-837页

作者： Said, Issam Fortin, Pierre Lamotte, Jean-Luc Calandra, Henri Sorbonne Univ Paris France Total E&P Houston TX USA

Oil and gas companies rely on high performance computing to process seismic imaging algorithms such as reverse time migration. graphics processing units are used to accelerate reverse time migration, but these deployments suffer from limitations such as the lack of high graphics processing unit memory capacity, frequent CPU-GPU communications that may be bottlenecked by the PCI bus transfer rate, and high power consumptions. Recently, AMD has launched the Accelerated processing unit (APU): a processor that merges a CPU and a graphics processing unit on the same die featuring a unified CPU-GPU memory. In this paper, we explore how efficiently may the APU be applicable to reverse time migration. Using OpenCL (along with MPI and OpenMP), a CPU/APU/GPU comparative study is conducted on a single node for the 3D acoustic reverse time migration, and then extended on up to 16 nodes. We show the relevance of overlapping the I/O and MPI communications with the computations for the APU and graphics processing unit clusters, that performance results of APUs range between those of CPUs and those of graphics processing units, and that the APU power efficiency is greater than or equal to the graphics processing unit one.

关键词： Reverse time migration exploration geophysics graphics processing unit computing hybrid architectures power efficiency

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MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU

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IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2017年第3期21卷 867-874页

作者： Katsigiannis, Stamos Zacharia, Eleni Maroulis, Dimitris Univ Athens Dept Informat & Telecommun Real Time Syst & Image Anal Grp Athens 15703 Greece

Complementary DNA (cDNA) microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images that often suffer from noise, artifacts, and uneven background. In this study, the MIGS-GPU [Microarray Image Gridding and Segmentation on graphics processing unit (GPU)] software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the GPU by means of the compute unified device architecture (CUDA) in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a user-friendly interface that requiresminimum input in order to run.

关键词： Compute unified device architecture (CUDA) DNA microarrays graphics processing unit computing grow-cut microarray gridding microarray segmentation

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Fast multiview three-dimensional reconstruction method using cost volume filtering

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OPTICAL ENGINEERING 2014年第3期53卷 1-10页

作者： Lee, Seung Joo Park, Min Ki Jang, In Yeop Lee, Kwan H. Gwangju Inst Sci & Technol Kwangju 500712 South Korea

As the number of customers who want to record three-dimensional (3-D) information using a mobile electronic device increases, it becomes more and more important to develop a method which quickly reconstructs a 3-D model from multiview images. A fast multiview-based 3-D reconstruction method is presented, which is suitable for the mobile environment by constructing a cost volume of the 3-D height field. This method consists of two steps: the construction of a reliable base surface and the recovery of shape details. In each step, the cost volume is constructed using photoconsistency and then it is filtered according to the multiscale. The multiscale-based cost volume filtering allows the 3-D reconstruction to maintain the overall shape and to preserve the shape details. We demonstrate the strength of the proposed method in terms of computation time, accuracy, and unconstrained acquisition environment. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： multiview three-dimensional reconstruction multiscale cost volume filtering graphics processing unit computing

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graphics-processing-unit-Accelerated Multiphase Computational Tool for Asteroid Fragmentation/Pulverization Simulation

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AIAA JOURNAL 2017年第2期55卷 599-609页

作者： Zimmerman, Ben J. Wie, Bong Iowa State Univ Dept Aerosp Engn 1200 Howe Hall Ames IA 50011 USA Iowa State Univ Asteroid Deflect Res Ctr Dept Aerosp Engn Ames IA 50011 USA

The simulation of asteroid target fragmentation or pulverization is a challenging task that demands efficient and accurate numerical methods with large computational power. To this end, the high-order spectral difference method is implemented with graphics-processing-unit computing. Hypervelocity kinetic-energy impactors are of practical interest, which generate high-pressure deformational shock waves in the target bodies upon impact. Due to the extremely short deformation time associated with hypervelocity impact, the material behaves in a similar manner to a compressible fluid, and the compressible Euler equations can be applied. To model the multiple material interactions, an n-phase equation model is adopted into the spectral difference method. All simulations presented are solved with graphics processing units, producing solutions orders of magnitude faster than the central-processing-unit counterpart. Several impact cases are compared, including a heavy impactor and multiple impactor system, against an asteroid target. Orbital dispersion effectiveness is evaluated, and results indicate that the multiple impactor system outperforms the single heavy impactor.

关键词： Asteroids graphics processing unit Central processing unit graphics processing unit computing Kinetic Energy Shock Front Compressible Fluid Euler Equations Computational Fluid Dynamics Pressure Coefficient

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Parallel GPU-accelerated adaptive mesh refinement on two-dimensional phase-field lattice Boltzmann simulation of dendrite growth

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COMPUTATIONAL MATERIALS SCIENCE 2022年 211卷

作者： Sakane, Shinji Aoki, Takayuki Takaki, Tomohiro Kyoto Inst Technol Fac Mech Engn Sakyo Ku Kyoto 6068585 Japan Tokyo Inst Technol Global Sci Informat & Comp Ctr 2-12-1-i7-3 OokayamaMeguro Ku Tokyo 1528550 Japan

Simulations of dendritic solidification involving melt convection and solid motion usually require a considerably higher computational domain than the dendrite size, whose computational efficiency with a uniform mesh is extremely low. In this study, to accelerate those two-dimensional simulations using the phase-field and lattice Boltzmann (PF-LB) methods, we developed a parallel computing method with multiple graphics processing units (GPUs) for the adaptive mesh refinement (AMR) method with dynamic load balancing (parallel-GPU AMR). It was confirmed that parallel-GPU AMR simulations were faster than those with the uniform mesh when the number of grid points in the adaptive mesh was around 40% or less than those in the uniform mesh. We also demonstrate that the developed parallel-GPU AMR can greatly accelerate the PF-LB simulations of dendrite growth with melt convection and solid motion.

关键词： Phase-field method Lattice Boltzmann method Solidification graphics processing unit computing Adaptive mesh refinement method

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Accelerated method for the optimization of quadratic image filter

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JOURNAL OF ELECTRONIC IMAGING 2019年第3期28卷 033036-033036页

作者： Uzun, Suleyman Akgun, Devrim Bilecik Seyh Edebali Univ Dept Comp Engn Bilecik Turkey Sakarya Univ Dept Comp Engn Sakarya Turkey

Quadratic image filter involves the second-order multiplications of an input image mask in addition to linear terms, and determining the weights of the quadratic filter using optimization methods requires intense computational power due to the cost of the resulting fitness function. A graphics processing unit (GPU)-based algorithm is proposed to determine quadratic image filter weights using genetic algorithms and particle swarm optimization methods. Since the most time consuming part of determining the mask weights using heuristic algorithms is the fitness computation process, the fitness computation process is designed to work on the GPU, and a significant acceleration is achieved. For this purpose, different designs such as direct method and population-based method have been developed within the GPU to minimize training time. According to experimental results, the proposed methods provide significant accelerations over sequential implementation. The first method computes the fitness function for each population member separately, and it produces about 43 times acceleration over the sequential implementation. The second method developed is based on the complete evaluation of the population, and it produces about 151 times acceleration over the sequential implementation. (C) 2019 SPIE and IS&T

关键词： quadratic image filters compute unified device architecture graphics processing unit computing Volterra filters

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