Task modules Partitioning, Scheduling and Floorplanning for Partially Dynamically Reconfigurable Systems Based on Modern Heterogeneous FPGAs
Modern field programmable gate array(FPGA) can be partially dynamically reconfigurable with heterogeneous resources distributed on the chip. And FPGA-based partially dynamically reconfigurable system(FPGA-PDRS) can be used to accelerate computing and improve computing flexibility. However, the traditional design of FPGA-PDRS is based on manual design. Implementing the automation of FPGA-PDRS needs to solve the problems of task modules partitioning, scheduling, and floorplanning on heterogeneous resources. Existing works only partly solve problems for the automation process of FPGA-PDRS or model homogeneous resource for FPGA-PDRS. To better solve the problems in the automation process of FPGA-PDRS and narrow the gap between algorithm and application, in this paper, we propose a complete workflow including three parts, pre-processing to generate the list of task modules candidate shapes according to the resources requirements, exploration process to search the solution of task modules partitioning, scheduling, and floorplanning, and post-optimization to improve the success rate of floorplan. Experimental results show that, compared with state-of-the-art work, the proposed complete workflow can improve performance by 18.7\%, reduce communication cost by 8.6\%, on average, with improving the resources reuse rate of the heterogeneous resources on the chip. And based on the solution generated by the exploration process, the post-optimization can improve the success rate of the floorplan by 14\%.
Code (0)
등록된 구현이 없습니다.
Tasks
SchedulingSimilar Papers 제목 키워드 기반
Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning
Analog integrated circuit (IC) floorplanning is typically a manual process with the placement of components (devices and modules) planned by a layout engineer. This process is further complicated by the interdependence o…
Transfer LearningPiano: A Multi-Constraint Pin Assignment-Aware Floorplanner
Floorplanning is a critical step in VLSI physical design, increasingly complicated by modern constraints such as fixed-outline requirements, whitespace removal, and the presence of pre-placed modules. In addition, the as…
One Step Beyond: Feedthrough & Placement-Aware Rectilinear Floorplanner
Floorplanning determines the shapes and locations of modules on a chip canvas and plays a critical role in optimizing the chip's Power, Performance, and Area (PPA) metrics. However, existing floorplanning approaches ofte…
Floorplanning of VLSI by Mixed-Variable Optimization
By formulating the floorplanning of VLSI as a mixed-variable optimization problem, this paper proposes to solve it by memetic algorithms, where the discrete orientation variables are addressed by the distribution evoluti…
FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models
Recent large language models (LLMs) have tended to leverage sparsity to reduce computations, employing the sparsely activated mixture-of-experts (MoE) technique. MoE introduces four modules, including token routing, toke…
GPUMixture-of-ExpertsScheduling