The Effects of Caching on Reconfigurable Adaptive Computing Systems

Abstract

Adaptive computing systems have proven useful for implementing a wide range of algorithms. A limitation of current systems is the relatively small amount of reconfigurable hardware resources. Many algorithms require more hardware resources than are available. One solution to this problem is runtime reconfiguration (RTR). Using RTR techniques, a large algorithm is implemented as a collection of configurations for the reconfigurable hardware. These configurations are loaded onto the reconfigurable hardware as necessary to implement the algorithm. A primary limitation of RTR is that the reconfiguration process is slow. Therefore, methods of decreasing reconfiguration time are desirable.

Another method of implementing large algorithms on small hardware is to use multiple configurable computing platforms connected via a communication network. RTR techniques can be used in conjunction with this method to further increase hardware availability. In this case reconfiguration time is increased by the overhead of transmitting data across the communication network. Methods of decreasing network overhead are desirable.

This thesis discusses the use of caching techniques to decrease reconfiguration time. An architecture for caching configurations is implemented on a configurable computing system platform. The use of caching to decrease network overhead is discussed and exhibited. An example application is implemented and used to evaluate the effects of caching on reconfiguration time and algorithm performance.