Author :
Daw, Nathaniel ; Goldstein, Seth ; Strelow, Dennis
Author_Institution :
Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Reconfigurable computing obtains its performance advantage over fixed processors by creating hardware configurations that are specialized for a particular application. In some cases, this advantage can be pushed even further, by creating hardware specialized to a particular instance of an application. For many problems where this approach is applicable, such as automatic target recognition, template matching and encryption, the problem parameters can change often, even within a single program execution, requiring periodic, and potentially expensive, hardware reconfigurations. To support these applications, we propose a method for on-chip configuration generation, or embedded compilation, for use with Carnegie Mellon University´s PipeRench reconfigurable processor. We describe PipeRench´s performance in detail for one problem, template matching, relative to the newest general-purpose processors, and show how embedded compilation can be used to support multiple problem instances for a second problem, IDEA encryption
Keywords :
cryptography; embedded systems; multimedia computing; pattern matching; pipeline processing; program compilers; reconfigurable architectures; IDEA encryption; PipeRench reconfigurable processor; automatic target recognition; embedded compilation; encryption; general-purpose processors; hardware reconfigurations; multimedia applications; multiple problem instances; on-chip configuration generation; performance; problem parameters; reconfigurable computing; specialized hardware configurations; template matching; Cryptography; Encoding; Fabrics; Hardware; Motion control; Motion estimation; Runtime; Target recognition; Timing; Tracking;