An Orthogonal Multiprocessor for Parallel Scientific Computations

A new multiprocessor architecture, called orthogonal multiprocessor (OMP), is proposed in this paper. This OMP architecture has a simplified busing structure and partially shared memory, which compares very favorably over fully shared-memory multiprocessors using crossbar switch, multiple buses, or multistage networks. The higher performance comes mainly from significantly increased memory bandwidth, fully exploited parallelism, reduced communication overhead, and lower hardware control complexities. Parallel algorithms being mapped include matrix arithmetic, linear system solver, FFT, array sorting, linear programming, and parallel PDE solutions. In most cases, linear speedup can be achieved on the OMP system. The OMP architecture provides linearly scalable performance and is well suited for building special-purpose scientific computers such as for signal/image processing, machine sorting, linear system solvers, and PDE machines, etc.