This award provides support to develop computing infrastructure in the areas of parallel languages and compilers, automatic parallelization of algorithms, computer vision, and simulation and synthesis of digital devices. The infrastructure consists of a state of the art Single Instruction Multiple Data (SIMD) computer along with support staff to ensure that the computer hardware and software are properly maintained. The parallel languages and compilers for parallel computers research focusses on the problem of the dependence of efficient software on the underlying parallel architecture. This dependence makes the development of portable software which is also efficient difficult and to date impossible. The research focusses on languages in which parallelism can be expressed free of architecture assumptions and compilers that will compile programs using these architecture free constructs into efficient code for specific parallel architectures. The automatic parallelization of algorithms research focusses on the problem of efficiently mapping algorithms to SIMD computers. The SIMD computer executes by having many processors execute the same instruction on different data. Thus the movement of data and the choice of which processors should execute an instruction is critical in order to obtain high performance. This research focusses on a software tool that can be adapted to a variety of SIMD architectures and which will perform the parallelization of algorithms to be used with these architectures. Computer vision and image processing have been ideal applications for SIMD computers because the processing of images can be broken down into the processing of sub-images, each sub-image algorithm being the same, followed by uniform data movement between processors. The computer vision research aims to develop a collection of algorithms for vision and image processing that will efficiently use the SIMD architecture. The research projects on the simulation and synthesis of digital devices use the processing power of the SIMD computer to perform tasks that would require supercomputer computational capabilities. These projects include the synthesis of digital diffractive elements and the simulation of the operation of semiconductor devices. The synthesis of digital diffractive elements, used in optics, requires substantial computational capabilities and input/output capacity (on the order of 10,000 hours on a VAX 780). Similarly the modeling of semiconductor devices requires substantial computational resources(the solution of order 30,000 sparse matrices). Both of these research projects propose to develop algorithms for use on the SIMD computer in order to obtain the computational capability necessary to solve problems of this magnitude. //
