Performance Evaluation of a Parallel Decoupled Data Driven Multiprocessor

摘要

The Decoupled Data-Driven (D{sup}3) architecture has shown promising results from performance evaluations based upon deterministic simulations. This paper provides performance evaluations of the D{sup}3 architecture through the formulation and analysis of a stochastic model. The D{sup}3 architecture is a hybrid control/dataflow approach that takes advantage of inherent parallelism present in a program by dynamically scheduling program threads based on data availability and it also takes advantage of locality through the use of conventional processing elements that execute the program threads. The model is validated by comparing the deterministic and stochastic model responses. After model validation, various input parameters are varied such as the number of available processing elements and average thread length, then the performance of the architecture is evaluated. The stochastic model is based upon a closed queuing network and utilizes the concepts of available parallelism and virtual queues in order to be reduced to a Markovian system. Experiments with varying computation engine thread lengths and communication latencies indicate a high degree of tolerance with respect to exploited parallelism.