Bandwidth Management in Application Mapping for Dynamically Reconfigurable Architectures

Abstract

Partial dynamic reconfiguration (often referred to as partial RTR) enables true on-demand computing. In an on-demand computing environment, a dynamically invoked application is assigned resources such as data bandwidth, configurable logic. The limited logic resources are customized during application execution by exploiting partial RTR. In this article, we propose an approach that maximizes application performance when available bandwidth and logic resources are limited. Our proposed approach is based on theoretical principles of minimizing application schedule length under bandwidth and logic resource constraints. It includes detailed microarchitectural considerations on a commercially popular reconfigurable device, and it exploits partial RTR very effectively by utilizing data-parallelism property of common image-processing applications. We present extensive application case studies on a cycle-accurate simulation platform that includes detailed resource considerations of the Xilinx Virtex XC2V3000. Our experimental results demonstrate that applying our proposed approach to common image-filtering applications leads to 15--20% performance gain in scenarios with limited bandwidth, when compared to prior work that also exploits data-parallelism with RTR but includes simpler bandwidth considerations. Last but not the least, we also demonstrate how our proposed theoretical principles can be directly applied to solve related problems such as minimizing schedule length under logic resource and power constraints.