Run-time optimization of a dynamically reconfigurable embedded system through performance prediction

Abstract

A key tool to increase the exploitation of dynamic reconfigurable platforms is the run-time resource manager. This system module coordinates the usage of both software and reconfigurable hardware resources in the context of a multi-programmed environment, by alleviating the operating system's induced overhead. This paper introduces a two-layers run-time resource manager for dynamic reconfigurable platforms. The upper level is composed of several application-level managers (one for each application) that provide the most suitable mapping based on resource constraints and performance prediction. The lower level is composed of a centralized system-level resource manager that assigns the HW/SW resources to each application. We present a video surveillance case study in which the proposed resource management technique outperforms the performance of the state of the art by 28% on average, introducing a computational time overhead within 2%

An Efficient Framework for Floor-plan Prediction of Dynamic Runtime Reconfigurable Systems

“…The closest published research to our work can be found in [19], [20], [21] and [22]. In [19], the authors presents a high level prediction modeling technique that produces prediction models for is cellaneous platforms and tool chains and application domains.…”

“…The work in [20] presents a framework consisting of two layers for resource management of dynamic reconfigurable platforms. The proposed system is capable of evaluating the performance of a reconfigurable computing platform based on prediction model.…”