权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Parallel Algorithm for 3D Particle Simulation using CM-2

使用 CM-2 进行 3D 粒子模拟的并行算法

基本信息

批准号：
05044078
负责人：
IKEBE Yasuhiko
金额：
$ 2.88万
依托单位：
University of Aizu (1995)University of Tsukuba (1993-1994)
依托单位国家：
日本
项目类别：
Grant-in-Aid for international Scientific Research
财政年份：
1993
资助国家：
日本
起止时间：
1993 至 1995
项目状态：
已结题

项目摘要

This report presents some new data parallel implementations of a plasma particle-in-cell (PIC) simulation code using a scan vector model, which is a strictly data parallel.Ever since the emergence of parallel computers, particle-in-cell (PIC) particle simulation has been recognized as a practical tool that scientists in disciplines such as fluid dynamics and plasma sciences can use to study the complex dynamics of such particles as air molecules or sub-atomic ions and electrons. Noted as one of the 'Grand Challenge' problems by U.S.Government agencies, the parallelizations of PIC codes have been promoted because PIC codes are assumed to possess inherent parallelism.A usual PIC code maps a spatial simulation domain onto a grid. Particles are represented as moving within the grid, while both the properties that are tracked by the grid points and by the particles are updated. On a parallel computer, one can embed either the particles or the grids onto the processors as the primary data structure. In the first case, each processor is responsible for tracing the properties associated with the assigned particles, which we will call the particle data. The properties tracked at the grid points, which we will call the grid data, are made available to the particles, which is so-called a 'gather' part of the computation. On the other hand, if the grid is chosen as the primary data structure, each processor is responsible for keeping track of a subsection of the simulation domain, and the particle data are made available to the grid points, which is so-called a 'scatter' part of the computation. In both the grid and particle processors, the load-balance and the communication costs should be carefully considered. We have successfully implemented a SPMD version of Scan Vector model PIC code in our research.

本文介绍了采用扫描矢量模型的等离子体粒子模拟程序的一些新的数据并行实现方法，它是一种严格的数据并行。胞内粒子粒子模拟已经被认为是一种实用的工具，流体动力学和等离子体科学等学科的科学家可以使用它来研究诸如空气等粒子的复杂动力学分子或亚原子离子和电子。PIC程序的并行化问题被美国政府列为“大挑战”问题之一，因为PIC程序具有内在的并行性，通常的PIC程序将空间模拟域映射到网格上。粒子表示为在网格内移动，而网格点和粒子跟踪的属性都将更新。在并行计算机上，可以将粒子或网格嵌入到处理器上作为主要数据结构。在第一种情况下，每个处理器负责跟踪与指定粒子相关的属性，我们将其称为粒子数据。在网格点处跟踪的属性（我们称之为网格数据）可供粒子使用，这就是所谓的计算的“聚集”部分。另一方面，如果选择网格作为主要数据结构，则每个处理器负责跟踪模拟域的子部分，并且粒子数据可用于网格点，这就是所谓的计算的“分散”部分。在网格和粒子处理器中，负载平衡和通信成本都应该仔细考虑。在我们的研究中，我们已经成功地实现了一个SPMD版本的扫描向量模型PIC代码。