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

本研究的目标是实现一种新的编程模型 分布式内存多处理器上的科学计算，称为 Lattice parallelism（LP）。 LP用于科学方法， 局部地非均匀地集中计算工作， 不可预测的，例如，自适应网格方法。 它提供 高级操作，以动态隐藏 操纵复杂的动态数据结构 的目标 这些研究是为了更好地理解格 在现实条件下的平行性;将其应用于科学 应用程序，并探索运行时优化技术。 的 LP的实施和评估将在英特尔 iPSC/860，运行各种应用程序代码在我们的处置。 格并行的一个新特性是它利用了 非均匀计算中存在的紧耦合局部结构 从而避免了高通信开销。 这在以下方面意义重大： 鉴于大规模并行分布式 内存多处理器，这是特别敏感的影响， 通信开销。 这项研究将导致开发一个软件工具， 减少了并行化全尺寸数值计算所需的工作量 一个数量级或更好的软件。

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.//