RIA: Lattice Parallelism: A Programming Model for Dynamically Manipulating Distributed Data Structures in Localized Non-Uniform Scientific Calculations

本研究的目标是在分布式内存多处理器上实现一种新的科学计算编程模型，称为格型并行(LP)。LP用于局部非均匀且不可预测地集中计算工作的科学方法，例如自适应网格方法。它提供高级操作来隐藏动态操作精细动态数据结构的低级细节。研究的目的是为了更好地理解现实条件下的格并行，将其应用于科学应用，并探索运行时优化技术。LP的实施和评估将在Intel iPSC/860上进行，运行各种应用代码供我们使用。格子并行的一个新特点是利用了非均匀计算中存在的紧密耦合的局部结构，从而避免了较高的通信开销。鉴于大规模并行分布式内存多处理器的最终出现，这一点意义重大，这些处理器对通信开销的影响特别敏感。这项研究将导致开发一种软件工具，以减少将全规模数值软件并行化所需的工作量降低一个数量级或更好。//

The goal of this research is to implement a new model for programming scientific computations on distributed memory multiprocessors, called lattice parallelism (LP). LP is intended for scientific methods that locally concentrate computational effort non-uniformly and unpredictably, for example, adaptive mesh methods. It provides high-level operations to hide the low-level details of dynamically manipulating elaborate, dynamic data structures. The objectives of the research are to gain a better understanding of lattice parallelism under realistic conditions; to apply it to scientific applications, and to explore run-time optimization techniques. The implementation and evaluation of LP will be carried out on the Intel iPSC/860, running a variety of application codes at our disposal. A novel feature of lattice parallelism is that it exploits the tightly coupled local structure present in non-uniform calculations and so avoids high communication overheads. This is significant in light of the ultimate emergence of massively parallel distributed memory multiprocessors, which are especially sensitive to the effects of communication overhead. This research will result in the development of a software tool for reducing the effort required to parallelize full scale numerical software by an order of magnitude or better.//