Xilinx XC4000系列FPGA互连资源自动测试软件生成和硬件平台搭建

随着FPGA的发展,FPGA测试技术也得到了很快地发展。因为FPGA的结构和传统专用集成电路有着本质的区别,在FPGA中不能形成可测性设计电路,但它的可编程能力决定了其测试电路可以通过编程的方法来实现。本文讨论了XilinxXC4000系列FPGA中互连资源的自动测试方法。提出了一种新的测试资源坐标定位方法,使得测试软件能够将测试配置转换成器件配置,并搭建了硬件测试平台,实现实体FPGA芯片测试。

基于SRAM的FPGA测试技术研究

半导体芯片的生产制造过程并不是完美无缺的，所有的芯片需要进行针对制造缺陷的测试。随着FPGA芯片规模越来越大，结构越来越复杂，产品测试也越来越困难。在FPGA测试所面临的主要问题是：对CLB、互连资源、IO资源等结构进行数学建模、测试配置算法和测试向量的开发、测试结构的选择、测试平台的搭建等。 本文主要工作及创新点如下： 根据FPGA的可配置逻辑单元的不同组成结构，给出了针对常规逻辑资源给出了8个测试配置达到100%覆盖率，，并提出了基于故障模型的可配置逻辑资源的测试方法，并在硬件测试平台中进行验证，证明了方法的有效性； 根据FPGA互连资源的结构建立模型，并运用着色算法得到测试配置，达到100%的测试覆盖率，并提出了一种测试配置到器件配置的新的转换方法，该方法简单易行。搭建了基于ATE的测试平台，通过这个平台实现了FPGA芯片互连资源测试方法，测试效果良好。 通过XC4000系列FPGA可配置逻辑单元和互连资源测试的研究，我们总结了适合FPGA测试的一般方法，可以应用在任何类型的FPGA测试中。 提出了一种针对开关矩阵多路选择器的测试配置方法和测试向量。并将这种方法推广到芯片级测试配置，提出了一种基于BIST的测试结构。这是因为FPGA芯片的IO端口有限，用BIST结构可以节省IO资源。

FPGA implementation of dual-microphone delay-and-sum beamforming for in-car speech enhancement and recognition

In an automotive environment, the performance of a speech recognition system is affected by environmental noise if the speech signal is acquired directly from a microphone. Speech enhancement techniques are therefore necessary to improve the speech recognition performance. In this paper, a field-programmable gate array (FPGA) implementation of dual-microphone delay-and-sum beamforming (DASB) for speech enhancement is presented. As the first step towards a cost-effective solution, the implementation described in this paper uses a relatively high-end FPGA device to facilitate the verification of various design strategies and parameters. Experimental results show that the proposed design can produce output waveforms close to those generated by a theoretical (floating-point) model with modest usage of FPGA resources. Speech recognition experiments are also conducted on enhanced in-car speech waveforms produced by the FPGA in order to compare recognition performance with the floating-point representation running on a PC.

The Spartan-3E Tutorial 1 : Introduction to FPGA Programming, Version 1.0

This tutorial is designed to help new users become familiar with using the Spartan-3E board. The tutorial steps through the following: writing a small program in VHDL which carries out simple combinational logic; connecting the program inputs and outputs to the switches, buttons and LEDs on the Spartan-3E board; and downloading the program to the Spartan-3E board using the Project Navigator software.

An FPGA-based approach to multi-objective evolutionary algorithm for multi-disciplinary design optimisation

This paper investigates the field programmable gate array (FPGA) approach for multi-objective and multi-disciplinary design optimisation (MDO) problems. One class of optimisation method that has been well-studied and established for large and complex problems, such as those inherited in MDO, is multi-objective evolutionary algorithms (MOEAs). The MOEA, nondominated sorting genetic algorithm II (NSGA-II), is hardware implemented on an FPGA chip. The NSGA-II on FPGA application to multi-objective test problem suites has verified the designed implementation effectiveness. Results show that NSGA-II on FPGA is three orders of magnitude better than the PC based counterpart.

FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

Computational experiments involving population size for FPGA-based implementation of a GA for the TSP

The feasibility of using an in-hardware implementation of a genetic algorithm (GA) to solve the computationally expensive travelling salesman problem (TSP) is explored, especially in regard to hardware resource requirements for problem and population sizes. We investigate via numerical experiments whether a small population size might prove sufficient to obtain reasonable quality solutions for the TSP, thereby permitting relatively resource efficient hardware implementation on field programmable gate arrays (FPGAs). Software experiments on two TSP benchmarks involving 48 and 532 cities were used to explore the extent to which population size can be reduced without compromising solution quality, and results show that a GA allowed to run for a large number of generations with a smaller population size can yield solutions of comparable quality to those obtained using a larger population. This finding is then used to investigate feasible problem sizes on a targeted Virtex-7 vx485T-2 FPGA platform via exploration of hardware resource requirements for memory and data flow operations.

Comparison of high level FPGA hardware design for solving tri-diagonal linear systems

Reconfigurable computing devices can increase the performance of compute intensive algorithms by implementing application specific co-processor architectures. The power cost for this performance gain is often an order of magnitude less than that of modern CPUs and GPUs. Exploiting the potential of reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) is typically a complex and tedious hardware engineering task. Re- cently the major FPGA vendors (Altera, and Xilinx) have released their own high-level design tools, which have great potential for rapid development of FPGA based custom accelerators. In this paper, we will evaluate Altera’s OpenCL Software Development Kit, and Xilinx’s Vivado High Level Sythesis tool. These tools will be compared for their per- formance, logic utilisation, and ease of development for the test case of a Tri-diagonal linear system solver.

Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware

Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

The Spartan-3E Tutorial 1 : Introduction to FPGA Programming, Version 2.0

This tutorial is designed to help new users become familiar with using the Spartan-3E board. The tutorial steps through: writing a small program in VHDL which carries out simple combinational logic; connecting the program inputs and outputs to the switches, buttons and LEDs on the Spartan-3E board; downloading the program to the Spartan-3E board using version 14.7 of the Xilinx ISE; and simulating the program using the iSim Simulator.

Hardware design and implementation of a MAVLink interface for an FPGA-based autonomous UAV flight control system

This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.