摘要
粒子输运的随机模拟方法通常用于求解大量运动状态中粒子的特征量。粒子输运问题广泛出现在医学、天体物理和核物理领域,当前粒子输运随机模拟求解方法的主要挑战是计算机能够支撑的模拟样本数、模拟时间尺度与研究人员研究实际问题的需求之间的差距。处理器性能的发展随着工艺尺寸进步的停滞进入了新的历史阶段,复杂的片上结构的集成已经不符合现今的要求。面向粒子输运程序,文中开展了一系列体系结构设计工作,通过分析和利用程序的并行性和访存特点,设计了精简内核和可重配置缓存来加速程序。通过模拟器验证,文中提出的体系结构相比传统乱序架构获得了4.45倍性能功耗比优势以及2.78倍性能面积比优势,这为进一步研究大规模众核粒子输运加速器奠定了基础。
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 4.5 x in performance per watt and 2.78 x in performance per area,which lays a foundation for the further study of large-scale many-nucleus particle transport acce-lerator.
作者
傅思清
黎铁军
张建民
FU Si-qing;LI Tie-jun;ZHANG Jian-min(School of Computer,National University of Defense Technology,Changsha 410073,China)
出处
《计算机科学》
CSCD
北大核心
2022年第6期81-88,共8页
Computer Science
基金
国家重点研发计划(2018YFB0204301)。
关键词
粒子输运
蒙特卡洛
体系结构
加速器
流水线
Particle transport
Monte Carlo
Architecture
Accelerator
Pipeline