Accelerating COBAYA3 on multi-core CPU and GPU systems using PARALUTION

被引:5
作者
Trost, Nico [1 ]
Jimenez, Javier [1 ]
Lukarski, Dimitar [2 ]
Sanchez, Victor [1 ]
机构
[1] Karlsruhe Inst Technol, Inst Neutron Phys & Reactor Technol, D-76344 Eggenstein Leopoldshafen, Germany
[2] Uppsala Univ, Dept Informat Technol, Div Comp Sci, S-75237 Uppsala, Sweden
关键词
COBAYA3; PARALUTION; Acceleration; Parallelization; Multi-core; GPUs;
D O I
10.1016/j.anucene.2014.08.005
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
COBAYA3 is a multi-physics system of codes which includes two 3D multi-group neutron diffusion codes, ANDES and COBAYA3-PBP, coupled with COBRA-TF, COBRA-IIIc and SUBCHANFLOW sub-channel thermal-hydraulic codes, for the simulation of LWR core transients. The 3D multi-group neutron diffusion equations are expressed in terms of a sparse linear system which can be solved using different iterative Krylov subspace solvers. The mathematical SPARSKIT library has been used for these purposes as it implements among others, external GMRES, PGMRES and BiCGStab solvers. Multi-core CPUs and graphical processing units (GPUs) provide high performance capabilities which are able to accelerate many scientific computations. To take advantage of these new hardware features in daily use computer codes, the integration of the PARALUTION library to solve sparse systems of linear equations is a good choice. It features several types of iterative solvers and preconditioners which can run on both multi-core CPUs and GPU devices without any modification from the interface point of view. This feature is due to the great portability obtained by the modular and flexible design of the library. By exploring this technology, namely the implementation of the PARALUTION library in COBAYA3, we are able to decrease the solution time of the sparse linear systems by a factor 5.15x on GPU and 2.56x on multi-core CPU using standard hardware. These obtained speedup factors in addition to the implementation details are discussed in this paper. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:252 / 259
页数:8
相关论文
共 50 条
  • [11] Accelerating Critical Section Execution with Asymmetric Multi-Core Architectures
    Suleman, M. Aater
    Mutlu, Onur
    Qureshi, Moinuddin K.
    Patt, Yale N.
    ACM SIGPLAN NOTICES, 2009, 44 (03) : 253 - 264
  • [12] Decision tree building on multi-core using FastFlow
    Aldinucci, Marco
    Ruggieri, Salvatore
    Torquati, Massimo
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2014, 26 (03) : 800 - 820
  • [13] Performance optimization of the MGB hydrological model for multi-core and GPU architectures
    Freitas, Henrique R. A.
    Mendes, Celso L.
    Ilic, Aleksandar
    ENVIRONMENTAL MODELLING & SOFTWARE, 2022, 148
  • [14] Accelerating Metric Space Similarity Joins with Multi-core and Many-core Processors
    Jin, Shichao
    Kim, Okhee
    Feng, Wenya
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2013, PT V, 2013, 7975 : 166 - 180
  • [15] Space Compression Algorithms Acceleration on Embedded Multi-core and GPU Platforms
    Jover-Alvarez A.
    Rodriguez I.
    Kosmidis L.
    Steenari D.
    Ada User Journal, 2022, 43 (02): : 129 - 132
  • [16] Study and Simulation of CPU Priority Scheduling Algorithm on Multi-core Processor Platform
    Fan, Ziguo
    Wang, Rongliang
    Yang, Penghao
    MANUFACTURING PROCESS AND EQUIPMENT, PTS 1-4, 2013, 694-697 : 2540 - 2544
  • [17] Scientific computations on multi-core systems using different programming frameworks
    Michailidis, Panagiotis D.
    Margaritis, Konstantinos G.
    APPLIED NUMERICAL MATHEMATICS, 2016, 104 : 62 - 80
  • [18] Batch Scheduler for Personal Multi-Core Systems
    Gupta, Prakhar
    Atrey, Tarun
    Garg, Manjari
    March, Verdi
    See, Simon Chong Wee
    PROCEEDINGS OF THE NINTH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING AND SCIENCE (DCABES 2010), 2010, : 584 - 587
  • [19] Task and Conduit Framework for Multi-Core Systems
    Mohindra, Sanjeev
    Daly, James
    Haney, Ryan
    Schrader, Glenn
    PROCEEDINGS OF THE HPCMP USERS GROUP CONFERENCE 2008, 2008, : 506 - 513
  • [20] Fast computation of 2D and 3D Legendre moments using multi-core CPUs and GPU parallel architectures
    Hosny, Khalid M.
    Salah, Ahmad
    Saleh, Hassan, I
    Sayed, Mahmoud
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2019, 16 (06) : 2027 - 2041