Acceleration of Electromagnetic Simulations on Reconfigurable FPGA Card

被引:0
|
作者
Topa, Tomasz [1 ]
Noga, Artur [1 ]
Stefanski, Tomasz P. [2 ]
机构
[1] Silesian Tech Univ, Dept Elect Elect Engn & Microelect, PL-44100 Gliwice, Poland
[2] Gdansk Univ Technol, Fac Elect Telecommun & Informat, PL-80233 Gdansk, Poland
来源
2023 30TH INTERNATIONAL CONFERENCE ON MIXED DESIGN OF INTEGRATED CIRCUITS AND SYSTEM, MIXDES | 2023年
关键词
Field programmable gate arrays; Hardware acceleration; Scientific computing; Electromagnetics;
D O I
10.23919/MIXDES58562.2023.10203273
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this contribution, the hardware acceleration of electromagnetic simulations on the reconfigurable field-programmable-gate-array (FPGA) card is presented. In the developed implementation of scientific computations, the matrix-assembly phase of the method of moments (MoM) is accelerated on the Xilinx Alveo U200 card. The computational method involves discretization of the frequency-domain mixed potential integral equation using the Rao-Wilton-Glisson basis functions and their extension to wire-to-surface junctions. Hardware resources in our FPGA card allow for synthesizing nine independent processing paths. The implementation is evaluated in a numerical test, which involves a simulation of radiation from a monopole antenna mounted on the roof of Dodge Shelby Charger car. Results show that the developed acceleration is 9.49x faster than a traditional (i.e., serial) central processing unit (CPU) MoM implementation, and about 1.66x faster than a parallel six-core CPU MoM implementation. However, in the considered numerical benchmark, the execution of the same computations on the hybrid CPU/FPGA platform reduces the power consumption 2.1x in comparison with the multicore implementation, hence, it allows for the reduction of environmental effects of scientific computing.
引用
收藏
页码:257 / 260
页数:4
相关论文
共 50 条
  • [1] RECONFIGURABLE DATABASE PROCESSOR FOR QUERY ACCELERATION ON FPGA
    Chen, Bo-En
    Lin, Bo-Yen
    Lai, Bo-Cheng
    2021 INTERNATIONAL SYMPOSIUM ON VLSI DESIGN, AUTOMATION AND TEST (VLSI-DAT), 2021,
  • [2] I/O card combines ADC with reconfigurable FPGA
    Webb, W
    EDN, 2002, 47 (18) : 13 - 13
  • [3] FPGA acceleration for HPC supercapacitor simulations
    Prouveur, Charles
    Haefele, Matthieu
    Kenter, Tobias
    Voss, Nils
    PROCEEDINGS OF THE PLATFORM FOR ADVANCED SCIENTIFIC COMPUTING CONFERENCE, PASC 2023, 2023,
  • [4] Realization of Rocket processor based on FPGA acceleration card
    Min, Shuyang
    Lie, Chen
    Xu, Ning
    PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020), 2020, : 990 - 994
  • [5] COMPUTATION ACCELERATION ON SGI RASC: FPGA BASED RECONFIGURABLE COMPUTING HARDWARE
    Jamro, Ernest
    Janiszewski, Marcin
    Machaczek, Krzysztof
    Russek, Pawel
    Wiatr, Kazimierz
    Wielgosz, Maciej
    COMPUTER SCIENCE-AGH, 2008, 9 : 21 - 34
  • [6] FAWS: FPGA Acceleration of Large-Scale Wave Simulations
    Gourounas, Dimitrios
    Hanindhito, Bagus
    Fathi, Arash
    Trenev, Dimitar
    John, Lizy K.
    Gerstlauer, Andreas
    2023 IEEE 34TH INTERNATIONAL CONFERENCE ON APPLICATION-SPECIFIC SYSTEMS, ARCHITECTURES AND PROCESSORS, ASAP, 2023, : 76 - 84
  • [7] FPGA Hardware Acceleration of Monte Carlo Simulations for the Ising Model
    Ortega-Zamorano, Francisco
    Montemurro, Marcelo A.
    Alejandro Cannas, Sergio
    Jerez, Jose M.
    Franco, Leonardo
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2016, 27 (09) : 2618 - 2627
  • [8] GPU Acceleration of Linear Systems for Computational Electromagnetic Simulations
    Inman, Matthew J.
    Elsherbeni, Atef Z.
    2009 IEEE ANTENNAS AND PROPAGATION SOCIETY INTERNATIONAL SYMPOSIUM AND USNC/URSI NATIONAL RADIO SCIENCE MEETING, VOLS 1-6, 2009, : 541 - 544
  • [9] Reconfigurable Systolic-based Pyramidal Neuron Block for CNN Acceleration on FPGA
    Ahmed, Hossam O.
    Ghoneima, Maged
    Dessouky, Mohamed
    2020 IEEE 10TH INTERNATIONAL CONFERENCE ON SYSTEM ENGINEERING AND TECHNOLOGY (ICSET), 2020, : 179 - 184
  • [10] Energy Efficient Biomolecular Simulations with FPGA-based Reconfigurable Computing
    Nallamuthu, Ananth
    Smith, Melissa C.
    Hampton, Scott
    Agarwal, Pratul K.
    Alam, Sadaf R.
    PROCEEDINGS OF THE 2010 COMPUTING FRONTIERS CONFERENCE (CF 2010), 2010, : 83 - 84