Empirical characterization of the latency of long asynchronous pipelines with data-dependent module delays

Abstract

The paper has two aims: on one hand, to characterize the nature of the relationship between the latency of an asynchronous pipeline and the stage latencies when the latency of the stages is data-dependent. On the other hand, to find the closed-form expression which relates the mean value of the latency of the pipeline with the parameters which characterize the behaviour of the constituting stages. To attain these two goals, we have followed an empirical approach; we have developed a model of an asynchronous pipeline with n stages, the latency of the stages has been modelled using a probability density function and the pipeline behaviour has been simulated. From the results, we have defined linear equations which estimate the mean latency of the pipeline without needs of simulation. Finally, we have designed and implemented a 32/spl times/32 bit asynchronous pipelined multiplier, and we have tested the estimations on it.

J. Manuel Colmenar

Full Professor

My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.