Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (6): 81-88.doi: 10.11896/jsjkx.210600179

• High Performance Computing • Previous Articles     Next Articles

Architecture Design for Particle Transport Code Acceleration

FU Si-qing, LI Tie-jun, ZHANG Jian-min   

  1. School of Computer,National University of Defense Technology,Changsha 410073,China
  • Received:2021-06-22 Revised:2022-02-15 Online:2022-06-15 Published:2022-06-08
  • About author:FU Si-qing,born in 1996,postgraduate.His main research interests include computer architecture and high performance computing.
    LI Tie-jun,born in 1977,Ph.D,resear-cher,Ph.D supervisor,is a member of China Computer Federation.His main research interests include high perfor-mance computing and so on.
  • Supported by:
    National Key Research and Development Program of China(2018YFB0204301).

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Abstract: The stochastic simulation method of particle transport is usually used to solve the characteristic quantity of a large number of moving particles.Particle transport problems are widely found in the fields of medicine,astrophysics and nuclear phy-sics.The main challenge of current stochastic simulation methods for particle transport is the gap between the number of simulation samples supported by computers,the simulation timescale,and researchers’ needs to study practical problems.Since the development of processor performance has entered a new historical stage with the stagnation of process size progress,the integration of complex on-chip structures no longer meets the current requirements.For particle transport programs,this paper carries out a series of architecture design works.By analyzing and using the parallelism and access characteristics of the program,simplified kernel and reconfigurable cache are designed to speed up the program.Experiments show that compared to the traditional architecture composed of multiple out-of-order cores,this architecture can obtain more than 4.5x in performance per watt and 2.78x in performance per area,which lays a foundation for the further study of large-scale many-nucleus particle transport acce-lerator.

Key words: Accelerator, Architecture, Monte Carlo, Particle transport, Pipeline

CLC Number: 

  • TP302
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