GPU-Accelerated Simulation of Elastic Wave Propagation

被引:0
|
作者
Kadlubiak, Kristian [1 ]
Jaros, Jiri [1 ]
Treeby, Bredly E. [2 ]
机构
[1] Brno Univ Technol, Fac Informat Technol, Ctr Excellence IT4Innovat, Brno, Czech Republic
[2] UCL, Dept Med Phys & Biomed Engn, London, England
来源
PROCEEDINGS 2018 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS) | 2018年
基金
英国工程与自然科学研究理事会; 欧盟地平线“2020”;
关键词
Ultrasound simulations; Elastic model; Pseudospectral methods; k-Wave; CUDA; GPU; INTENSITY FOCUSED ULTRASOUND;
D O I
10.1109/HPCS.2018.00044
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Modeling of ultrasound waves propagation in hard biological materials such as bones and skull has a rapidly growing area of applications, e.g. brain cancer treatment planing, deep brain neurostimulation and neuromodulation, and opening blood brain barriers. Recently, we have developed a novel numerical model of elastic wave propagation based on the Kelvin-Voigt model accounting for linear elastic wave proration in heterogeneous absorption media. Although, the model offers unprecedented fidelity, its computational requirements have been prohibitive for realistic simulations. This paper presents an optimized version of the simulation model accelerated by the Nvidia CUDA language and deployed on the best GPUs including the Nvidia P100 accelerators present in the Piz Daint supercomputer. The native CUDA code reaches a speed-up of 5.4 when compared to the Matlab prototype accelerated by the Parallel Computing Toolbox running on the same GPU. Such reduction in computation time enables computation of large-scale treatment plans in terms of hours.
引用
收藏
页码:188 / 195
页数:8
相关论文
共 50 条
  • [1] PacketShader: A GPU-Accelerated Software Router
    Han, Sangjin
    Jang, Keon
    Park, KyoungSoo
    Moon, Sue
    ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2010, 40 (04) : 195 - 206
  • [2] GPU-accelerated molecular mechanics computations
    Anthopoulos, Athanasios
    Grimstead, Ian
    Brancale, Andrea
    JOURNAL OF COMPUTATIONAL CHEMISTRY, 2013, 34 (26) : 2249 - 2260
  • [3] GPU-accelerated computation of electron transfer
    Hoefinger, Siegfried
    Acocella, Angela
    Pop, Sergiu C.
    Narumi, Tetsu
    Yasuoka, Kenji
    Beu, Titus
    Zerbetto, Francesco
    JOURNAL OF COMPUTATIONAL CHEMISTRY, 2012, 33 (29) : 2351 - 2356
  • [4] GPU-Accelerated Finite Element Method
    Dziekonski, Adam
    Lamecki, Adam
    Mrozowski, Michal
    2016 IEEE MTT-S INTERNATIONAL CONFERENCE ON NUMERICAL ELECTROMAGNETIC AND MULTIPHYSICS MODELING AND OPTIMIZATION (NEMO), 2016,
  • [5] GPU-accelerated Monte Carlo simulation of particle coagulation based on the inverse method
    Wei, J.
    Kruis, F. E.
    JOURNAL OF COMPUTATIONAL PHYSICS, 2013, 249 : 67 - 79
  • [6] GPU-accelerated Monte Carlo simulation of MV-CBCT
    Shi, Mengying
    Myronakis, Marios
    Jacobson, Matthew
    Ferguson, Dianne
    Williams, Christopher
    Lehmann, Mathias
    Baturin, Paul
    Huber, Pascal
    Fueglistaller, Rony
    Lozano, Ingrid Valencia
    Harris, Thomas
    Morf, Daniel
    Berbeco, Ross, I
    PHYSICS IN MEDICINE AND BIOLOGY, 2020, 65 (23)
  • [7] GPU-accelerated molecular dynamics simulation of solid covalent crystals
    Hou, Chaofeng
    Ge, Wei
    MOLECULAR SIMULATION, 2012, 38 (01) : 8 - 15
  • [8] GPU-Accelerated Batch Electromechanical Transient Simulation of Power System
    Wang, Yi
    Sun, Licheng
    Wang, Ziheng
    Feng, Yanjun
    PROCEEDINGS OF 2019 INTERNATIONAL FORUM ON SMART GRID PROTECTION AND CONTROL (PURPLE MOUNTAIN FORUM), VOL II, 2020, 585 : 673 - 684
  • [9] GPU-accelerated level-set segmentation
    Julián Lamas-Rodríguez
    Dora B. Heras
    Francisco Argüello
    Dagmar Kainmueller
    Stefan Zachow
    Montserrat Bóo
    Journal of Real-Time Image Processing, 2016, 12 : 15 - 29
  • [10] GPU-ACCELERATED SIMULATION OF A ROTARY VALVE BY THE DISCRETE ELEMENT METHOD
    Fuvesi, Balazs
    Ulbert, Zsolt
    HUNGARIAN JOURNAL OF INDUSTRY AND CHEMISTRY, 2019, 47 (02): : 31 - 42