Configuration Sharing Optimized Placement and Routing

Reconfigurable systems have been shown to achieve very high computational performance. However, the overhead associated with reconfiguration of hardware remains a critical factor in overall system performance. This paper discusses the development and evaluation of a technique to minimize the delay associated with reconfiguration based upon optimized sharing of configuration bit streams between design contexts. This is achieved through modified placement and routing algorithms

Swarm Intelligence for Digital Circuits Implementation on Field Programmable Gate Arrays Platforms

Field programmable gate arrays (FPGAs) are becoming increasingly important implementation platforms for digital circuits. One of the necessary requirements to effectively utilize the FPGA\u27s resources is an efficient placement and routing mechanism. This paper presents an optimization technique based on swarm intelligence for FPGA placement and routing. Mentor graphics technology mapping netlist file is used to generate initial FPGA placements and routings which are then optimized by particle swarm optimization (PSO). Results for the implementation of a binary coded decimal bidirectional counter and an arithmetic logic unit on a Xilinx FPGA show that PSO is a potential technique for solving the placement and routing problem

Placement and routing for reconfigurable systems.

Applications using reconfigurable logic have been widely demonstrated to offer better performance over software-based solutions. However, good performance rating is often destroyed by poor reconfiguration latency - time required to reconfigure hardware to perform the new task. Recent research focus on design automation techniques to address reconfiguration latency bottleneck. The contribution to novelty of this thesis is in new placement and routing techniques resulting in minimising reconfiguration latency of reconfigurable systems. This presents a part of design process concerned with positioning and connecting design blocks in a logic gate array. The aim of the research is to optimise the placement and interconnect strategy such that dynamic changes in system functionality can be achieved with minimum delay. A review of previous work in the field is given and the relevant theoretical framework developed. The dynamic reconfiguration problem is analysed for various reconfigurable technologies. Several algorithms are developed and evaluated using a representative set of problem domains to assess their effectiveness. Results obtained with novel placement and routing techniques demonstrate configuration data size reduction leading to significant reconfiguration latency improvements

Coarse-grained reconfigurable array architectures

Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code

Design synthesis for dynamically reconfigurable logic systems

Dynamic reconfiguration of logic circuits has been a research problem for over four decades. While applications using logic reconfiguration in practical scenarios have been demonstrated, the design of these systems has proved to be a difficult process demanding the skills of an experienced reconfigurable logic design expert. This thesis proposes an automatic synthesis method which relieves designers of some of the difficulties associated with designing partially dynamically reconfigurable systems. A new design abstraction model for reconfigurable systems is proposed in order to support design exploration using the presented method. Given an input behavioural model, a technology server and a set of design constraints, the method will generate a reconfigurable design solution in the form of a 3D floorplan and a configuration schedule. The approach makes use of genetic algorithms. It facilitates global optimisation to accommodate multiple design objectives common in reconfigurable system design, while making realistic estimates of configuration overheads and of the potential for resource sharing between configurations. A set of custom evolutionary operators has been developed to cope with a multiple-objective search space. Furthermore, the application of a simulation technique verifying the lll results of such an automatic exploration is outlined in the thesis. The qualities of the proposed method are evaluated using a set of benchmark designs taking data from a real reconfigurable logic technology. Finally, some extensions to the proposed method and possible research directions are discussed

Choose-Your-Own Adventure: A Lightweight, High-Performance Approach To Defect And Variation Mitigation In Reconfigurable Logic

For field-programmable gate arrays (FPGAs), fine-grained pre-computed alternative configurations, combined with simple test-based selection, produce limited per-chip specialization to counter yield loss, increased delay, and increased energy costs that come from fabrication defects and variation. This lightweight approach achieves much of the benefit of knowledge-based full specialization while reducing to practical, palatable levels the computational, testing, and load-time costs that obstruct the application of the knowledge-based approach. In practice this may more than double the power-limited computational capabilities of dies fabricated with 22nm technologies. Contributions of this work: • Choose-Your-own-Adventure (CYA), a novel, lightweight, scalable methodology to achieve defect and variation mitigation • Implementation of CYA, including preparatory components (generation of diverse alternative paths) and FPGA load-time components • Detailed performance characterization of CYA – Comparison to conventional loading and dynamic frequency and voltage scaling (DFVS) – Limit studies to characterize the quality of the CYA implementation and identify potential areas for further optimizatio