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.
