Evaluation of Parallel Decomposition Methods for Biomechanical Optimizations

Evaluation of parallel decomposition methods for biomechanical optimizations.

As the complexity of musculoskeletal models continues to increase, so will the computational demands of biomechanical optimizations. For this reason, parallel biomechanical optimizations are becoming more common. Most implementations parallelize the optimizer. In this study, an alternate approach is investigated that parallelizes the analysis function (i.e., a kinematic or dynamic simulation) c...

Optimizations for Parallel

This paper presents algorithms for reducing the communication overhead for parallel C programs that use dynamically-allocated data structures. The framework consists of an analysis phase called possible-placement analysis, and a transformation phase called communication selection. The fundamental idea of possible-placement analysis is to nd all possible points for insertion of remote memory ope...

Parallel Domain Decomposition Methods for Parabolic Equations

Locality and Parallel Optimizations for Parallel Supercomputing

Although processor speeds have been increasing rapidly over the past decade, the speed of memory has failed to keep pace. Memory is no longer fast enough to feed the processor enough data to keep it constantly busy. As a result, computations involving large data sets find themselves being slowed down not by a lack of processing power, but by frequent accessing of items in main memory and in pag...

Locality Optimizations for Parallel Machines

This paper focuses on the problem of locality optimizations for high-performance uniprocessor and multiprocessor systems. It shows that the problems of minimizing interprocessor communication and optimizing cache locality can be formulated in a similar manner. It outlines the algorithms to optimize for the various levels of the memory hierarchy simultaneously.