Seiler, E. J. | Search NASA

NASA NTRS1990

A parallel particle-in-cell model for the massively parallel processor

The availability of the nearest-neighbor communication-incorporating Massively Parallel Processor has prompted the development of a two-dimensional, particle-in-cell algorithm which loads particles in a cell randomly onto a row of processors, filling only half of them with particles. Due to the simplification of communications among processors achieved in a row by the vacant processors and the random-particle sequence, the algorithm efficiently sorts particles and performs gather/scatter procedures for collecting charge density according to their cells. The algorithm calculates electric fields at the cells by FFT.

Lin, C. S.↗

NASA NTRS1987

Synthetic aperture radar signal processing on the MPP

Satellite-borne Synthetic Aperture Radars (SAR) sense areas of several thousand square kilometers in seconds and transmit phase history signal data several tens of megabits per second. The Shuttle Imaging Radar-B (SIR-B) has a variable swath of 20 to 50 km and acquired data over 100 kms along track in about 13 seconds. With the simplification of separability of the reference function, the processing still requires considerable resources; high speed I/O, large memory and fast computation. Processing systems with regular hardware take hours to process one Seasat image and about one hour for a SIR-B image. Bringing this processing time closer to acquisition times requires an end-to-end system solution. For the purpose of demonstration, software was implemented on the present Massively Parallel Processor (MPP) configuration for processing Seasat and SIR-B data. The software takes advantage of the high processing speed offered by the MPP, the large Staging Buffer, and the high speed I/O between the MPP array unit and the Staging Buffer. It was found that with unoptimized Parallel Pascal code, the processing time on the MPP for a 4096 x 4096 sample subset of signal data ranges between 18 and 30.2 seconds depending on options.

Ramapriyan, H. K.↗