There is a growing national need to provide researchers with highspeed and cost-effective computers capable of handling computation-intensive statistical and forecasting problems. Examples of such statistical analyses include bootstrapping and projection pursuit regression. While supercomputers are often needed to speed the solution for these problems, there are problems associated with supercomputer use. These include limited availability and a high cost for routine application. The use of a commercially-available digital signal processor (DSP) chip offers a low-cost alternative to many of these problems. However, its application will require new algorithms capable of exploiting the unique features of this device. This program addresses research to evaluate the feasibility of using the DSP as a high performance coprocessor configured to perform statistical computations at speeds approaching that of lower end supercomputers. In the initial research, the building blocks necessary for statistical computation will be selected. From this, optimized algorithms and hardware/software configurations for DSP use will be determined based on analytical, simulation, and experimental results. The result of all phases of the project will be a low-cost tool for high-speed statistical computation.The potential commercial application as described by the awardee: There are potential applications of the proposed approach in research laboratories, commercial enterprises, and other areas where economical high-speed statistical computing is needed.
