Integrated Optimization of Partitioning, Scheduling and Floorplanning for Partially Dynamically Reconfigurable Systems

TL;DR

This paper presents an integrated optimization framework for task partitioning, scheduling, and floorplanning on partially dynamically reconfigurable FPGAs, improving performance and resource utilization through a novel representation and search method.

Contribution

It introduces a partitioned sequence triple (P-ST) representation and a simulated annealing-based search for efficient co-optimization of partitioning, scheduling, and floorplanning.

Findings

Efficient O(n^2) computation of floorplanning and scheduling from P-ST.

Effective exploration of design space using simulated annealing.

Experimental results show improved optimization performance.

Abstract

Confronted with the challenge of high performance for applications and the restriction of hardware resources for field-programmable gate arrays (FPGAs), partial dynamic reconfiguration (PDR) technology is anticipated to accelerate the reconfiguration process and alleviate the device shortage. In this paper, we propose an integrated optimization framework for task partitioning, scheduling and floorplanning on partially dynamically reconfigurable FPGAs. The partitions, schedule, and floorplan of the tasks are represented by the partitioned sequence triple P-ST (PS,QS,RS), where (PS,QS) is a hybrid nested sequence pair (HNSP) for representing the spatial and temporal partitions, as well as the floorplan, and RS is the partitioned dynamic configuration order of the tasks. The floorplanning and scheduling of task modules can be computed from the partitioned sequence triple P-ST in O(n^2) time. To integrate the exploration of the scheduling and floorplanning design space, we use a simulated annealing-based search engine and elaborate a perturbation method, where a randomly chosen task module is removed from the partition sequence triple and then inserted back into a proper position selected from all the (n+1)^3 possible combinations of partitions, schedule and floorplan. The experimental results demonstrate the efficiency and effectiveness of the proposed framework.