On-Chip Intrinsic Evolution Methodology for Sequential Logic Circuit Design

This paper focuses on the application of Virtual Reconfigurable Circuit (VRC) design methodology and intrinsic evolution for the design of small sequential circuits and their implementation on a single programmable chip with an embedded hardcore processor. The evolutionary algorithm is developed in software that runs on the embedded processor. Fitness function is calculated using hardware architecture and is used to guide the evolution process. This new method is applied to the development of a 3-bit sequence detector and the evolved architecture is implemented on a Xilinx™ Virtex-II pro device. Simulations were run on the evolved architecture and on the same circuit designed using conventional Hardware Descriptive Language (HDL). Both designs showed the same functional behavior. Synthesis results show that the new method can be used in successfully implementing small sequential circuits on a reconfigurable hardware environment

VHDL IMPLEMENTATION OF GENETIC ALGORITHM FOR 2-BIT ADDER

Future planetary and deep space exploration demands that the space vehicles should have robust system architectures and be reconfigurable in unpredictable environment. The Evolutionary design of electronic circuits, or Evolvable hardware (EHW), is a discipline that allows the user to automatically obtain the desired circuit design. The circuit configuration is under control of Evolutionary algorithms. The most commonly used evolutionary algorithm is Genetic Algorithm. The paper discusses on Cartesian Genetic Programming for evolving gate level designs and proposes Evolvable unit for 2-bit adder based on Genetic Algorithm

An Evolvable Combinational Unit for FPGAs

A complete hardware implementation of an evolvable combinational unit for FPGAs is presented. The proposed combinational unit consisting of a virtual reconfigurable circuit and evolutionary algorithm was described in VHDL independently of a target platform, i.e. as a soft IP core, and realized in the COMBO6 card. In many cases the unit is able to evolve (i.e. to design) the required function automatically and autonomously, in a few seconds, only on the basis of interactions with an environment. A number of circuits were successfully evolved directly in the FPGA, in particular, 3-bit multipliers, adders, multiplexers and parity encoders. The evolvable unit was also tested in a simulated dynamic environment and used to design various circuits specified by randomly generated truth tables

Evolvable circuit with transistor-level reconfigurability

An evolvable circuit includes a plurality of reconfigurable switches, a plurality of transistors within a region of the circuit, the plurality of transistors having terminals, the plurality of transistors being coupled between a power source terminal and a power sink terminal so as to be capable of admitting power between the power source terminal and the power sink terminal, the plurality of transistors being coupled so that every transistor terminal to transistor terminal coupling within the region of the circuit comprises a reconfigurable switch

Accelerating FPGA-based evolution of wavelet transform filters by optimized task scheduling

Adaptive embedded systems are required in various applications. This work addresses these needs in the area of adaptive image compression in FPGA devices. A simplified version of an evolution strategy is utilized to optimize wavelet filters of a Discrete Wavelet Transform algorithm. We propose an adaptive image compression system in FPGA where optimized memory architecture, parallel processing and optimized task scheduling allow reducing the time of evolution. The proposed solution has been extensively evaluated in terms of the quality of compression as well as the processing time. The proposed architecture reduces the time of evolution by 44% compared to our previous reports while maintaining the quality of compression unchanged with respect to existing implementations. The system is able to find an optimized set of wavelet filters in less than 2 min whenever the input type of data changes

Hardware Accelerator of Cartesian Genetic Programming with Multiple Fitness Units

A new accelerator of Cartesian genetic programming is presented in this paper. The accelerator is completely implemented in a single FPGA. The proposed architecture contains multiple instances of virtual reconfigurable circuit to evaluate several candidate solutions in parallel. An advanced memory organization was developed to achieve the maximum throughput of processing. The search algorithm is implemented using the on-chip PowerPC processor. In the benchmark problem (image filter evolution) the proposed platform provides a significant speedup (170) in comparison with a highly optimized software implementation. Moreover, the accelerator is 8 times faster than previous FPGA accelerators of image filter evolution

Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper

A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback

The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described

Evolutionary Technique for Automated Synthesis of Electronic Rircuits

A method of evolving a circuit uses a heterogenous mix of models of both high and low levels of resolution