Described is the Connection Machine, a massively parallel SIMD (single instruction multiple data) computer of 64K processors, used to simulate optical scattering and absorption phenomena where the scattering objects are much larger than the wavelength of the incident light. One processor of the connection machine is assigned to an individual incident ray. The processor tracks the ray through the object system noting the multiple reflections and refractions which occur. The results calculated are the vectors of the outgoing rays which are leaving the object system environment. As each of the interactions of each incident ray are independent of those of all other rays, 64K incident rays can be tracked at a time. The classic communication bottleneck between processors on SIMD machines is nonexistent in this case. Using a stochastic approach, a Monte Carlo technique is used whereby each ray is either reflected or refracted based on probabilities. The object is represented by a collection of small facets enabling almost any shaped object or objects to be modeled from any orientation. The limit on the complexity of the object system is limited only by the size of the host memory of the Connection Machine. The algorithm is such that it runs in linear time to the number of facets which are used to represent the system.>

Algorithms suitable for use on parallel computers are being developed to simulate the scattering and absorption of light by small penetrable objects such as ice crystals and biological cells. The solution of the problem is based on a geometrical optics approach. Each incident ray undergoes multiple reflections and refractions as it travels through the scattering object. Data parallel algorithms have been developed which assign one processor to each incident ray. A massively parallel architecture consisting of 64 K processors (the Connection Machine) is being used. This means that the scattering calculations for over 65000 rays can be carried out simultaneously. Using a stochastic approach, a Monte Carlo technique is used whereby each ray is either reflected or refracted based on probabilities.>

This paper presents parallel realizations of the two-dimensional reduced update Kalman filter. It is shown that sufficiently spaced pixels on certain diagonals may be predicted and updated in parallel. This parallelism is then exploited on a conventional shared memory parallel processor and timings are reported. Predicted performance is provided for area-array SIMD type parallel processors, e.g. CLIP4 and CLIP7.