Abstract
Asynchronous systems are attracting the interest of the designer community because of several useful features for sub-micron technologies: process-variation tolerant, low-power, removal of the clock tree generation, etc. One of the main problems for the simulation of these systems is the variable computation delays of their modules, that compute as fast as possible under the actual conditions of the system. This behavior complicates the high-level simulation of such systems and it is the main reason for the lack of simulation tools devoted to asynchronous microarchitectures. In this paper we present a modeling method useful for this kind of systems that describes the variable computation delay of an asynchronous circuit by using probability distribution functions. This method is deployed in an architectural simulator of a 64-bit superscalar asynchronous microarchitecture where the computation delay of each one of the modules of the microarchitecture was characterized through a probability distribution function. The experimental results show that the asynchronous behavior is successfully modeled, and the architectural simulations of standard benchmarks is affordable in terms of wall-clock simulation time.
J. Manuel Colmenar
Associate 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.