Equipment in Support of Parallel Processing Research

该奖项是为了将NCUBE并行处理器升级到 下一代NCUBE处理器。 研究项目在 计算机辅助的并行分级模拟系统 设计，信号处理的并行迭代算法，以及 并行有限元方法 升级后的NCUBE处理器 为了解决真实的世界问题。 90年代的计算挑战是将并行性投入工作 解决重要的计算密集型问题。 下一 一波超级计算机将使用数千到数百万个 单个处理器并行工作以解决问题。 那里 必须有某种机制来平均分配工作， 处理器，以充分利用并行性。 这项研究着眼于三个问题领域，特别适合 对于每个处理器具有其自己的存储器的并行体系结构 执行自己的程序 第一个项目是信号 用于医学图像重建的处理。 是非常重要 最高质量的图像可用于诊断目的， 运行在快速并行处理器上的好的并行算法是 为了实现这种医学图像重建 技术. 第二个项目涉及设计和仿真 超大规模集成电路 这是一个特别计算密集的 一个足够模块化的过程，这样就可以在一个 NCUBE处理器。 需要升级才能运行模拟 真实的超大规模集成电路。 最后一个项目是探索一套 有限元法是一种用于局部 微分方程解 这些技术，当 并行化，可能会表现出禁止通信成本之间 单独的计算元素。 额外的内存和 新的NCUBE处理器上更好的通信允许进一步 探索这些数值求解技术。

This award is for the upgrade of an NCUBE parallel processor to the next generation NCUBE processor. The research projects are in parallel hierarchical simulation systems for use in computer-aided design, parallel iterative algorithms for signal processing, and parallel finite element methods. The upgraded NCUBE processor is necessary in order to tackle real world problems. The computing challenge of the 90's is to put parallelism to work in solving important computational intensive problems. The next wave of super computers will be using thousands to millions of individual processors working in parallel to solve problems. There must be some mechanism to split the work up evenly amongst the processors in order to utilize parallelism to the fullest extent. This research looks at three problem domains particularly suited for parallel architectures where each processor has its own memory and executes its own program. The first project is signal processing for medical image reconstruction. It is very important the highest quality images be available for diagnostic purposes and good parallel algorithms running on a fast parallel processor are required in order to implement this medical image reconstruction technology. The second project involves the design and simulation of VLSI circuits. This is a particularly computation intensive process that is modular enough so that it can be programmed on an NCUBE processor. The upgrade is needed to run the simulations on real VLSI circuits. The final project is the exploration of a set of techniques known as finite element methods for partial differential equation solution. These techniques, when parallelized, may exhibit a prohibitive communication cost between the individual computing elements. The additional memory and better communications on the new NCUBE processor allows further exploration of these numerical solution techniques.