Partial dynamic reconfiguration (often referred to as partial RTR) enables true on-demand computing. A dynamically invoked application is assigned resources such as data bandwidth, configurable logic, and the limited logic resources are customized during application execution with partial RTR. In this work, we present key theoretical principles for maximizing application performance when available bandwidth is limited. We exploit bandwidth very effectively by selecting a suitable clock frequency for each task and maximize performance with partial RTR by exploiting data-parallelism property of common image-processing tasks. Our theoretical principles are integrated in our scheduling strategy, SCHEDRTR. We present detailed application case studies on a cycle-accurate simulation platform that addresses micro architectural concerns and includes detailed resource considerations of the Virtex XC2V3000 device. Our results demonstrate that applying SCHEDRTR to common image-filtering applications leads to 15--20% performance gain in scenarios with limited bandwidth, when compared to a sophisticated RTR scheduling strategy with data-parallelism but simpler bandwidth considerations.
['Sudarshan Banerjee', 'Elaheh Bozorgzadeh', 'Juanjo Noguera', 'Nikil Dutt']
Selective Band width and Resource Management in Scheduling for Dynamically Reconfigurable Architectures