Title of Presentation:
Primary (Corresponding) Author: Aravind Dasu
Organization of Primary Author:
Co-Authors: Jonathan Phillips
Abstract: Autonomous dynamic event scheduling, using Iterative Repair techniques such as those employed by
Iterative Repair problems are generally solved using a combinatorial search heuristic, such as Simulated Annealing (which is used by CASPER and ASPEN), Genetic Algorithms, or Stochastic Beam Search. All of these methods operate by gradually improving an initial solution over hundreds or thousands of iterations. We propose an FPGA-based architectural framework derived from ANSI C function-level blocks for accelerating these computations. At a function level, 99% of the work done by any Simulated Annealing algorithm is the repeated execution of three high-level steps: (1) generating a new solution, (2) evaluating the solution, and (3) determining whether the new solution should be accepted. The specifics of how each step operates vary with the application, and are implemented in VHDL through data- and control-flow analysis of the source C code. We present an ASIP implementation of Iterative Repair using Simulated Annealing and compare its performance with that of conventional sequential processors.