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Evolvable, reconfigurable hardware for future space systems

This paper overviews Evolvable Hardware (EHW) technology, examining its potential for enhancing survivability and flexibility of future space systems. EHW refers to selfconfiguration of electronic hardware by evolutionary/genetic search mechanisms. Evolvable Hardware can maintain existing functionality in the presence of faults and degradations due to aging, temperature and radiation. It can also configure itself for new functionality when required for mission changes or encountered opportunities. The paper illustrates hardware evolution in silicon using a JPL-designed programmable device reconfigurable at transistor level as the platform and a genetic algorithm running on a DSP as the reconfiguration mechanism. Rapid reconfiguration allows convergence to circuit solutions in the order of seconds. The experiments demonstrate functional recovery from faults as well as from degradation at extreme temperatures indicating the possibility of expanding the operational range of extreme electronics through evolved circuit solutions.

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Mixtrinsic Evolution

This paper introduces a third approach to Evolvable Hardware (EHW) called mixtrinsic EHW (MEHW).

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EHW Approach to Temperature Compensation of Electronics

Efforts are under way to apply the concept of evolvable hardware (EHW) to compensate for variations, with temperature, in the operational characteristics of electronic circuits. To maintain the required functionality of a given circuit at a temperature above or below the nominal operating temperature for which the circuit was originally designed, a new circuit would be evolved; moreover, to obtain the required functionality over a very wide temperature range, there would be evolved a number of circuits, each of which would satisfy the performance requirements over a small part of the total temperature range. The basic concepts and some specific implementations of EHW were described in a number of previous NASA Tech Briefs articles, namely, "Reconfigurable Arrays of Transistors for Evolvable Hardware" (NPO-20078), Vol. 25, No. 2 (February 2001), page 36; Evolutionary Automated Synthesis of Electronic Circuits (NPO- 20535), Vol. 26, No. 7 (July 2002), page 37; "Designing Reconfigurable Antennas Through Hardware Evolution" (NPO-20666), Vol. 26, No. 7 (July 2002), page 38; "Morphing in Evolutionary Synthesis of Electronic Circuits" (NPO-20837), Vol. 26, No. 8 (August 2002), page 31; "Mixtrinsic Evolutionary Synthesis of Electronic Circuits" (NPO-20773) Vol. 26, No. 8 (August 2002), page 32; and "Synthesis of Fuzzy-Logic Circuits in Evolvable Hardware" (NPO-21095) Vol. 26, No. 11 (November 2002), page 38. To recapitulate from the cited prior articles: EHW is characterized as evolutionary in a quasi-genetic sense. The essence of EHW is to construct and test a sequence of populations of circuits that function as incrementally better solutions of a given design problem through the selective, repetitive connection and/or disconnection of capacitors, transistors, amplifiers, inverters, and/or other circuit building blocks. The connection and disconnection can be effected by use of field-programmable transistor arrays (FPTAs). The evolution is guided by a search-andoptimization algorithm (in particular, a genetic algorithm) that operates in the space of possible circuits to find a circuit that exhibits an acceptably close approximation of the desired functionality. The evolved circuits can be tested by mathematical modeling (that is, computational simulation) only, tested in real hardware, or tested in combinations of computational simulation and real hardware.

Stoica, Adrian↗

Transistor Level Circuit Experiments using Evolvable Hardware

The Jet Propulsion Laboratory (JPL) performs research in fault tolerant, long life, and space survivable electronics for the National Aeronautics and Space Administration (NASA). With that focus, JPL has been involved in Evolvable Hardware (EHW) technology research for the past several years. We have advanced the technology not only by simulation and evolution experiments, but also by designing, fabricating, and evolving a variety of transistor-based analog and digital circuits at the chip level. EHW refers to self-configuration of electronic hardware by evolutionary/genetic search mechanisms, thereby maintaining existing functionality in the presence of degradations due to aging, temperature, and radiation. In addition, EHW has the capability to reconfigure itself for new functionality when required for mission changes or encountered opportunities. Evolution experiments are performed using a genetic algorithm running on a DSP as the reconfiguration mechanism and controlling the evolvable hardware mounted on a self-contained circuit board. Rapid reconfiguration allows convergence to circuit solutions in the order of seconds. The paper illustrates hardware evolution results of electronic circuits and their ability to perform under 230 C temperature as well as radiations of up to 250 kRad.

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Evolvable Hardware for Space Applications

This paper focuses on characteristics and applications of evolvable hardware (EHW) to space systems, and describes research directions and ongoing work at JPL.

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Evolutionary design of smart analog circuits

This paper discusses the use of Evolvable Hardware (EHW) in automatic synthesis of electronic circuits for computational intelligence (CI) hardware.

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Polymorphic Electronic Circuits

Polymorphic electronics is a nascent technological discipline that involves, among other things, designing the same circuit to perform different analog and/or digital functions under different conditions. For example, a circuit can be designed to function as an OR gate or an AND gate, depending on the temperature (see figure). Polymorphic electronics can also be considered a subset of polytronics, which is a broader technological discipline in which optical and possibly other information- processing systems could also be designed to perform multiple functions. Polytronics is an outgrowth of evolvable hardware (EHW). The basic concepts and some specific implementations of EHW were described in a number of previous NASA Tech Briefs articles. To recapitulate: The essence of EHW is to design, construct, and test a sequence of populations of circuits that function as incrementally better solutions of a given design problem through the selective, repetitive connection and/or disconnection of capacitors, transistors, amplifiers, inverters, and/or other circuit building blocks. The evolution is guided by a search-and-optimization algorithm (in particular, a genetic algorithm) that operates in the space of possible circuits to find a circuit that exhibits an acceptably close approximation of the desired functionality. The evolved circuits can be tested by computational simulation (in which case the evolution is said to be extrinsic), tested in real hardware (in which case the evolution is said to be intrinsic), or tested in random sequences of computational simulation and real hardware (in which case the evolution is said to be mixtrinsic).

Stoica, Adrian↗

Scalability, Timing, and System Design Issues for Intrinsic Evolvable Hardware

In this paper we address several issues pertinent to intrinsic evolvable hardware (EHW). The first issue is scalability; namely, how the design space scales as the programming string for the programmable device gets longer. We develop a model for population size and the number of generations as a function of the programming string length, L, and show that the number of circuit evaluations is an O(L2) process. We compare our model to several successful intrinsic EHW experiments and discuss the many implications of our model. The second issue that we address is the timing of intrinsic EHW experiments. We show that the processing time is a small part of the overall time to derive or evolve a circuit and that major improvements in processor speed alone will have only a minimal impact on improving the scalability of intrinsic EHW. The third issue we consider is the system-level design of intrinsic EHW experiments. We review what other researchers have done to break the scalability barrier and contend that the type of reconfigurable platform and the evolutionary algorithm are tied together and impose limits on each other.

Hereford, James↗

2nd & 3rd Generation Vehicle Subsystems

This paper contains viewgraph presentation on the "2nd & 3rd Generation Vehicle Subsystems" project. The objective behind this project is to design, develop and test advanced avionics, power systems, power control and distribution components and subsystems for insertion into a highly reliable and low-cost system for a Reusable Launch Vehicles (RLV). The project is divided into two sections: 3rd Generation Vehicle Subsystems and 2nd Generation Vehicle Subsystems. The following topics are discussed under the first section, 3rd Generation Vehicle Subsystems: supporting the NASA RLV program; high-performance guidance & control adaptation for future RLVs; Evolvable Hardware (EHW) for 3rd generation avionics description; Scaleable, Fault-tolerant Intelligent Network or X(trans)ducers (SFINIX); advance electric actuation devices and subsystem technology; hybrid power sources and regeneration technology for electric actuators; and intelligent internal thermal control. Topics discussed in the 2nd Generation Vehicle Subsystems program include: design, development and test of a robust, low-maintenance avionics with no active cooling requirements and autonomous rendezvous and docking systems; design and development of a low maintenance, high reliability, intelligent power systems (fuel cells and battery); and design of a low cost, low maintenance high horsepower actuation systems (actuators).

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Design Space Issues for Intrinsic Evolvable Hardware

This paper discuss the problem of increased programming time for intrinsic evolvable hardware (EHW) as the complexity of the circuit grows. We develop equations for the size of the population, n, and the number of generations required for the population to converge, ngen, based on L, the length of the programming string. We show that the processing time of the computer becomes negligible for intrinsic EHW since the selection/crossover/mutation steps are only done once per generation, suggesting there is room for use of more complex evolutionary algorithms m intrinsic EHW. F i y , we review the state of the practice and discuss the notion of a system design approach for intrinsic EHW.

Hereford, James↗

Evolvable Electronic Systems

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Evolvable Systems hardware engineered electronics ↗

Design Space Issues for Intrinsic Evolvable Hardware

This paper discusses the problem of increased programming time for intrinsic evolvable hardware (EM) as the complexity of the circuit grows. As the circuit becomes more complex, then more components will be required and a longer programming string, L, is required. We develop equations for the size of the population, n, and the number of generations required for the population to converge, based on L. Our analytical results show that even though the design search space grows as 2L (assuming a binary programming string), the number of circuit evaluations, n*ngen, only grows as O(Lg3), or slightly less than O(L). This makes evolvable techniques a good tool for exploring large design spaces. The major hurdle for intrinsic EHW is evaluation time for each possible circuit. The evaluation time involves downloading the bit string to the device, updating the device configuration, measuring the output and then transferring the output data to the control processor. Each of these steps must be done for each member of the population. The processing time of the computer becomes negligible since the selection/crossover/mutation steps are only done once per generation. Evaluation time presently limits intrinsic evolvable hardware techniques to designing only small or medium-sized circuits. To evolve large or complicated circuits, several researchers have proposed using hierarchical design or reuse techniques where submodules are combined together to form complex circuits. However, these practical approaches limit the search space of available designs and preclude utilizing parasitic coupling or other effects within the programmable device. The practical approaches also raise the issue of why intrinsic EHW techniques do not easily apply to large design spaces, since the analytical results show only an O(L) complexity growth.

Hereford, James↗