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Multiphysics coupling in the Exascale computing project

INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2022年第1期36卷 3-4页

作者： Evans, Thomas M. White, Julia C. Oak Ridge Natl Lab Nucl Energy & Fuel Cycles Div HPC Methods Nucl Applicat Grp Oak Ridge TN USA Oak Ridge Natl Lab 1 Bethel Valley Rd Oak Ridge TN 37831 USA

Multiphysics coupling presents a significant challenge in terms of both computational accuracy and performance. Achieving high performance on coupled simulations can be particularly challenging in a high-performance computing context. The US Department of Energy Exascale Computing Project has the mission to prepare mission-relevant applications for the delivery of the exascale computers starting in 2023. Many of these applications require multiphysics coupling, and the implementations must be performant on exascale hardware. In this special issue we feature six articles performing advanced multiphysics coupling that span the computational science domains in the Exascale Computing Project.

关键词： Exascale computing project graphical processing unit computational physics applications programming models

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A survey of software implementations used by application codes in the Exascale Computing Project

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2022年第1期36卷 5-12页

作者： Evans, Thomas M. Siegel, Andrew Draeger, Erik W. Deslippe, Jack Francois, Marianne M. Germann, Timothy C. Hart, William E. Martin, Daniel F. Oak Ridge Natl Lab Oak Ridge TN USA Argonne Natl Lab 9700 S Cass Ave Argonne IL 60439 USA Lawrence Livermore Natl Lab Livermore CA USA Lawrence Berkeley Natl Lab Berkeley CA USA Los Alamos Natl Lab Washington DC USA Sandia Natl Labs Livermore CA USA

The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages-C, C++, and Fortran-and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.

关键词： Exascale Computing Project graphical processing unit computational physics applications programming models

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Development of a real-time wave field reconstruction TEM system (II): correction of coma aberration and 3-fold astigmatism, and real-time correction of 2-fold astigmatism

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MICROSCOPY 2018年第1期67卷 37-45页

作者： Tamura, Takahiro Kimura, Yoshihide Takai, Yoshizo Osaka Univ Grad Sch Engn Dept Mat & Life Sci 2-1 Yamada Oka Suita Osaka 5650871 Japan

In this study, a function for the correction of coma aberration, 3-fold astigmatism and real-time correction of 2-fold astigmatism was newly incorporated into a recently developed real-time wave field reconstruction TEM system. The aberration correction function was developed by modifying the image-processing software previously designed for auto focus tracking, as described in the first article of this series. Using the newly developed system, the coma aberration and 3-fold astigmatism were corrected using the aberration coefficients obtained experimentally before the processing was carried out. In this study, these aberration coefficients were estimated from an apparent 2-fold astigmatism induced under tilted-illumination conditions. In contrast, 2-fold astigmatism could be measured and corrected in real time from the reconstructed wave field. Here, the measurement precision for 2-fold astigmatism was found to be +/- 0.4 nm and +/- 2 degrees. All of these aberration corrections, as well as auto focus tracking, were performed at a video frame rate of 1/30 s. Thus, the proposed novel system is promising for quantitative and reliable in situ observations, particularly in environmental TEM applications.

关键词： real-time observation wave field reconstruction coma aberration 3-fold astigmatism 2-fold astigmatism graphical processing unit

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PARALLELIZATION, PROCESSOR COMMUNICATION AND ERROR ANALYSIS IN LATTICE KINETIC MONTE CARLO

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SIAM JOURNAL ON NUMERICAL ANALYSIS 2014年第3期52卷 1156-1182页

作者： Arampatzis, Giorgos Katsoulakis, Markos A. Plechac, Petr Univ Crete Dept Appl Math Hellas Greece Fdn Res & Technol Hellas Greece Univ Massachusetts Dept Math & Stat Amherst MA 01003 USA Univ Delaware Dept Math Sci Newark DE 19716 USA

In this paper we study from a numerical analysis perspective the fractional step kinetic Monte Carlo (FS-KMC) algorithms proposed in [G. Arampatzis, M. A. Katsoulakis, P. Plechac, M. Taufer, and L. Xu, J. Comput. Phys., 231 (2012), pp. 7795-7814] for the parallel simulation of spatially distributed particle systems on a lattice. FS-KMC are fractional step algorithms with a time-stepping window Delta t, and as such they are inherently partially asynchronous since there is no processor communication during the period Delta t. In this contribution we primarily focus on the error analysis of FS-KMC algorithms as approximations of conventional, serial KMC. A key aspect of the presented analysis relies on emphasizing a goal-oriented approach for suitably defined macroscopic observables (e.g., density, energy, correlations, surface roughness), rather than focusing on strong topology estimates for individual trajectories. The presented error analysis allows us to compare different parallelization strategies and their processor communications by relating the algorithm partial asynchrony to the time step Delta t and a prescribed error tolerance. Finally, the presented results show that previously developed KMC algorithms based on domain decomposition principles also allow for simulations with controlled errors for macroscopic of observables, while their partial asynchrony also can be demonstrated and quantified.

关键词： kinetic Monte Carlo method parallel algorithms Markov semigroups operator splitting partially asynchronous algorithms graphical processing unit GPU

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ASELGPU: FPGA-based OpenGL SC compatible DO-254 certifiable graphics processor engine

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SIGNAL IMAGE AND VIDEO processing 2023年第4期17卷 1607-1613页

作者： Eral, Goksan Kilinc, Cudi Akkul, Erdem Safa Kiziloz, Cemil ASELSAN Inc TR-06750 Ankara Turkey

In modern aircraft cockpits, display units are used for human-computer interactions, such as Primary Flight Display (PFD). Development of these safety-critical units is liable to avionic standards such as DO-254, which must be satisfied for an aircraft's electronic hardware. In this paper, we propose DO-254 compliant OpenGL Secure Library (SC) 1.1 implemented purely in Hardware Description Language (HDL) for graphical processing units used in aircraft: ASELGPU. ASELGPU is an FPGA-based, scalable, low-latency, fully parallel architecture that supports full OpenGL pipeline, including fixed-point vertex processing, rasterization, texture mapping, and frame buffering. Additionally, ASELGPU contains a highly efficient caching mechanism for texture mapping, and parallel rasterization for geometric primitives. Our architecture provides the generation of different kinds of avionics displays such as PFD, and 2D/3D map at high resolution and frame rates through various digital video interfaces such as Display Port, A818, and HD-SDI.

关键词： OpenGL Field programmable gate arrays graphical processing unit Avionics

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Optimization Methods for Virtual Screening on Novel Computational Architectures

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CURRENT COMPUTER-AIDED DRUG DESIGN 2011年第1期7卷 44-52页

作者： Perez-Sanchez, Horacio Wenzel, Wolfgang Karlsruhe Inst Technol Inst Nanotechnol D-76344 Eggenstein Leopoldshafen Germany

The numerous virtual screening (VS) methods that are used today in drug discovery processes differ mainly by the way they model the receptor and/or ligand and by the approach to perform screening. All these methods have in common that they screen databases of chemical compounds containing up to millions of ligands i.e. ZINC database. Larger databases increase the chances of generating hits or leads, but the computational time needed for the calculations increases not only with the size of the database but also with the accuracy of the VS method and the model. Fast docking methods with atomic resolution require a few minutes per ligand, while molecular dynamics-based approaches still require hundreds or thousands of hours per ligand. Therefore, the limitations of VS predictions are directly related to a lack of computational resources, a major bottleneck that prevents the application of detailed, high-accuracy models to VS The current increase in available computer power at low cost due to novel computational architectures would enhance considerably the performance of the different VS methods and the quality and quantity of the conclusions we can get from screening. In this review, we will discuss recent trends in modeling techniques which, in combination with novel hardware platforms, yield order-of-magnitude improvements in the processing speeds of VS methods. We show the state of the art of VS methods as applied with novel computational architectures and the current trends of advanced computing.

关键词： Virtual screening optimization cell processor graphical processing unit drug discovery drug design FPGA

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Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs Fast What-If Analyses of Localized and Dynamic Effects

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JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE 2021年第3期101卷 357-370页

作者： Perumalla, Kalyan S. Alam, Maksudul Oak Ridge Natl Lab Oak Ridge TN 37830 USA

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what-if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what-if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what-if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what-if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what-if scenarios several orders of magnitude faster than the conventional methods.

关键词： What-if analyses Decision trees Complex systems Incremental simulation graphical processing unit Simulation cloning Epidemic models

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Efficient GPU-based implementations of simplex type algorithms

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APPLIED MATHEMATICS AND COMPUTATION 2015年 250卷 552-570页

作者： Ploskas, Nikolaos Samaras, Nikolaos Univ Macedonia Sch Informat Sci Dept Appl Informat Thessaloniki 54006 Greece

Recent hardware advances have made it possible to solve large scale Linear Programming problems in a short amount of time. graphical processing units (GPUs) have gained a lot of popularity and have been applied to linear programming algorithms. In this paper, we propose two efficient GPU-based implementations of the Revised Simplex Algorithm and a Primal-Dual Exterior Point Simplex Algorithm. Both parallel algorithms have been implemented in MATLAB using MATLAB's Parallel Computing Toolbox. Computational results on randomly generated optimal sparse and dense linear programming problems and on a set of benchmark problems (netlib, kennington, Meszaros) are also presented. The results show that the proposed GPU implementations outperform MATLAB's interior point method. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Linear Programming Simplex type algorithms graphical processing unit Parallel Computing MATLAB

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Accelerating the numerical simulation of magnetic field lines in tokamaks using the GPU

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FUSION ENGINEERING AND DESIGN 2011年第4-5期86卷 399-406页

作者： Kalling, R. C. Evans, T. E. Orlov, D. M. Schissel, D. P. Maingi, R. Menard, J. E. Sabbagh, S. A. Gen Atom Co San Diego CA 92186 USA Univ Calif San Diego La Jolla CA 90093 USA Oak Ridge Natl Lab Oak Ridge TN 37831 USA Princeton Plasma Phys Lab Princeton NJ 08543 USA Columbia Univ Appl Phys & Math Dept New York NY 10027 USA

TRIP3D is a field line simulation code that numerically integrates a set of nonlinear magnetic field line differential equations. The code is used to study properties of magnetic islands and stochastic or chaotic field line topologies that are important for designing non-axisymmetric magnetic perturbation coils for controlling plasma instabilities in future machines. The code is very computationally intensive and for large runs can take on the order of days to complete on a traditional single CPU. This work describes how the code was converted from Fortran to C and then restructured to take advantage of GPU computing using NVIDIA's CUDA. The reduction in computing time has been dramatic where runs that previously took clays now take hours allowing a scale of problem to be examined that would previously not have been attempted. These gains have been accomplished without significant hardware expense. Performance, correctness, code flexibility, and implementation time have been analyzed to gauge the success and applicability of these methods when compared to the traditional multi-CPU approach. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Stochastic magnetic field lines graphical processing unit General-purpose computation on graphical processing units Tokamaks NSTX Non-axisymmetric magnetic perturbations

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Accelerating Group Fusion for Ligand-Based Virtual Screening on Multi-core and Many-core Platforms

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JOURNAL OF INFORMATION processing SYSTEMS 2016年第4期12卷 724-740页

作者： Mohd-Hilmi, Mohd-Norhadri Al-Laila, Marwah Haitham Malim, Nurul Hashimah Ahamed Hassain Univ Sains Malaysia Sch Comp Sci George Town Malaysia

The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized.

关键词： Chemoinformatics graphical processing unit Group Fusion Open Multiprocessing Virtual Screening

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