Report on the Second NASA/DoD Workshop
on Evolvable Hardware

IEEE Transactions on
Evolutionary Computation

Vol. 5, No. 3, June 2001


Hugo de Garis

Head of the Brain Builder Group,
Starlab, Brussels, Belgium.
degaris@starlab.net
http://foobar.starlab.net/~degaris



The second annual NASA/DoD Workshop on Evolvable Hardware (EH-2000), took place on July 13-15, 2000, in Palo Alto, California, USA, sponsored by NASA and DARPA (Defense Advanced Research Projects Agency), and co-hosted by NASA Ames (Information Sciences and Technology Directorate), the JPL (Jet Propulsion Lab) Center for Integrated Space Microsystems (CISM), and the JPL Center for Space Microelectronics Technology (CSMT), and with the cooperation of various other divisions of NASA Ames.

The very fact that these evolvable hardware workshops are now an annual event shows clearly that the field has been established solidly in the U.S., after America's initial four-year delay behind Switzerland.


The Workshop

About 90 people from 11 different countries attended the workshop. (This was down from the 130 who attended the prior workshop in 1999.) The three-day workshop was held fully in plenary session. The invited talks were spread over the three days, but most occured during the first morning. Once the invited talks concluded, most of which will be highlighted below, the submitted paper talks were divided into the following eight topics, which give an indication of how the EH field is evolving in human terms.

1. Algorithms
2. From Biology to Robotics
3. Evolvability
4. Evolution of Analog and Mixed Signal Circuits
5. Evolution of Digital Functions
6. Reconfiguration Architecture and Devices
7. Evolution of CA and Brain-Inspired Architecture
8. Real World Applications


Highlights of the Workshop

First, I will cover the invited speakers.


1. Steve Zornetzer (NASA) - "NASA's future will depend on EH"

What struck me initially about the 2nd NASA/DoD EH workshop was the very impressive public relations job its organizers had done on their managements in the year since the 1st workshop. In particular, Adrian Stoica from JPL and Jason Lohn from NASA Ames (two of the driving forces of EH in the U.S.) and others, had persuaded their superiors of the importance of this new research field for the future of NASA and for the future of space travel in general. For example, Dr. Steve Zornetzer, Director of the NASA Ames Information Systems and Technology Directorate, made a very strong statement in his kickoff speech, "Maybe NASA's future will depend on evolvable hardware." Zornetzer has the reputation of supporting very innovative research, such as nanotechnology, which he did several years before it became main stream. His brief introductory talk asked the question, "Why is NASA interested in EH?" I found his answers very persuasive and promising for the future development of EH in the U.S. in general and for space in particular. He said that future planetary and deep space exploration over the next 20-30 years will demand that the space vehicles have robust system architectures and be dynamically reconfigurable. Current technologies cannot cope, he said, because they are just not robust enough.

Future space missions will send probes into the saline oceans under Europa's ice cap. How can such an unpredictable environment be explored? Obviously with autonomous, real-time robots, which must be robust, dynamically reconfigurable, and not brittle. It is impractical for NASA to send up triply redundant systems to ensure reliability because the weight problem makes that too expensive. Future architectures need to be adaptive to uncertain environments. EH may have a major role to play in this regard. Zornetzer's vision is to develop three broad areas of competence, 1) space technology, 2) nanotech, and 3) information technology. He has set up a newly funded, Intelligent Systems (IS) program ($70M/yr), and a Space Biology program, which researches biologically-based systems for space. He also set up a nanotech initiative. IS includes automated reasoning, human-centered computing, and revolutionary computing (e.g. quantum computing, neural nets, evolvable hardware, etc.). Space biology includes understanding biological principles, the functioning of nanotubes, EH, etc. The nanotech initiative is seen as a requirement for future NASA missions, to revolutionize electronics, for autonomous microrovers, mini helicopters, etc. The IS initiative received 500-600 proposals. The space biology initiative went out for January 2001, and the nano proposal will be announced in 2001. There are other funding programs which are unsolicited.


2. Nikzad Toomarian (JPL) - "EH for 100+ year space probe survival"

The second institutional speaker was Toomarian of JPL, who made rather similar remarks to Zornetzer's, such as "EH is needed for deep space exploration in extreme environments (-150 to 300 degrees)." He stressed that the various planned space missions, such as the Pluto express, launch date 2004, with a flight time of 8-9 years, and later interstellar explorations, will need to emphasise long term survivability and evolvability. He wants to see furture space hardware systems based on nature's adaptibility that can re-evolve themselves in seconds. He wants EH for 100+ years survival of space systems with low power and high intelligence.


3. Carver Mead - "I've been doing EH all my life"

Mead, who is in his mid 60s, is famous in electronics circles. He virtually invented most of its modern approaches. He's had several research careers in four fields, 1) device physics (smaller transistors, MOSFETs), 2) VLSI design methodology (silicon boundaries), 3) biological electronics, neuromorphic scaling behavior (silicon cochlea and retina), and 4) collective electrodynamics (with a new book to come out on this). He said he had founded 23 startup companies and that in a sense "I have been doing EH all my life." He designed his first chip in 1971, a programmable logic array, PLA, while being involved with Texas Instruments and Hewlett Packard at the same time. His 2nd chip had an analog output. Then he was into CPLDs (complex programmable logic devices), programmable state machines, data path elements, and the beginnings of RISC (reduced instruction set computer). He spoke of how the density of wiring can overwhelm chip design, and the need for good wire scaling. This was in the early 80s, when harbinging the FPGA (field programmable gate array). Also in the early 80s he got involved with Richard Feynman, the famous quantum electrodynamics theorist, and the physics of computation.

Mead got hooked on the idea of trying to get electronics to do what brains do, resulting in the development of a system that performs inner product learning autonomously and in real time - hence his famous silicon retina and cochlea. This led to his interest in reusable, configurable, and self-configurable HW that can learn from the environment, performing analog processing on floating silicon gates and do neuron-like things. He feels that Lamarckian processing (i.e., genetic inheritance of socially acquired characteristics) is the way to go. We, that is humanity, cannot wait millions of years for slow Darwinian evolution as a paradigm for building evolvable systems. He is very interested in brain functioning, asking how a human baby learns about the world. A baby's nervous system proliferates early, and later the neurons/synapses die off. Learning is the change in synaptic strengths. All these phenomena have analog and digital properties. The mutation of genes is digital but the influence of the environment on the genes is analog. There is lots of analog stuff in the brain, he said. He spoke about the neural code, i.e., the relative time of arrival of various neural signals. Neural signals are self clocking. There is no global clock. In dendritic trees, synapses form nonlinear analog interactions of pulses. It's the coincidences that evolve. Certain combinations of pulses at the dendritic trees are reinforced, the rest are not significant. A fly's brain does more than the best computer. He felt that the evolution of the brain follows a gradient into a higher-dimensional space. It uses a neural code and is robust. If 10% of the neurons die, that has no effect. The brain is not brittle.

He spoke of the duplication of genes as a means of evolution. One gene is modified by mutation while the other is intact. Sometimes the modified gene is used, so some experimentation is tried. Perhaps the brain areas were duplicated and experimented with. He felt that the so called "junk DNA" is not junk, but rather a library of old ideas. He felt the discrete and the continuous analog aspects of the brain play a role. In the discrete space of genes, one can copy and pass on the information and not lose information. In learning, one has continuous gradients of computing structure. These two processes should be integrated he felt. He even got into a bit of quantum theory. With electron tunneling, he felt some systems could take advantage of wave functions overlapping to create one large wave function. His views on the link between QM (quantum mechanics) and biology were not clear to me. He finished his talk by saying that the electronics field could make some "awesome devices using bio tricks."

It was wonderful to hear this brilliant famous man, with a solid electronics background, talking with such passion and knowledge about the brain and evolution. He had obviously spent a lot of his time in recent years studying these fields, providing further proof of how interdisciplinary the most creative minds are becoming lately.


4. Michael Conrad (Wayne State) - "The father of molecular computing"

Conrad, who passed away in December 2000 due to an illness with cancer, was the pioneer of molecular computing and was famous for that. He was head of the Biocomputing Group at Wayne State University, in Detroit. One of his major goals was to get molecules to compute. Conrad gave a talk on his latest work with his grad students on getting molecules to compute. It was not an easy talk to follow for someone unfamiliar with the field. It was factually dense, and the listener sensed that the man was trying to summarise a life's work in half an hour. He mentioned that molecules perform according to a "shape-based pattern recognition" paradigm. Shape-based systems are now buildable he said. Molecules need to be big enough for lock and key pattern recognition. They explore each other thanks to Brownian motion. Molecules are not sloppy, they are discrete, with lots of nonlinear dynamics. They are built in a precise manner. The way they fold depends on their milieu. Molecules allow for conformational signal processing and conformational signal fusion, which can lead to macroscopic action, e.g., a neuron firing. One can send in chemical signals to molecules which cause conformational change, which results in an output. These ideas can be implemented in an enzymatic pattern processing flow system, using the enzymes as the pattern recognizers. He used such a system (and I had trouble with the details, not being a molecular biologist nor a biochemist) to perform Boolean operations such as OR, XOR, NAND, etc. The processing is context sensitive. He admitted that programmability is a conceptual bottle neck at the moment in molecular- or bio-computing. He also said that a lot of evolutionary work is needed to make molecular computing useful, and that it will take years of researchers time to develop it.


5. Tetsuya Higuchi (ETL) - "E-Hard finds its killer-ap"

Higuchi is one of the pillars of the EH community, having been one of the field's founding fathers. He began his EH work by evolving GAL chips, but extrinsically, not intrinsically, i.e., he simulated the evolution in software. He did not evolve directly in the chip itself. Higuchi's approach to EH has been very applied for the past few years. He is getting MITI (the Japanese Ministry of International Trade and Industry) money to pursue his research within his "Evolvable Hardware Systems" group at ETL. (http://www.etl.go.jp/~ehw/) His talk was entitled "Evolvable Hardware for Industrial Applications" which reflects his primary interests. For several years Higuchi has been saying that "for the EH field to survive it will need to find its "killer ap" (big selling application)." I think it's fair to make several remarks here. The first is that the field is doing just fine, judging by the number of researchers and groups listed in Adrian Thompson's EH list (http://www.cogs.susx.ac.uk/users/adrianth/EHW_groups.html) I counted 48 entries (22 Jan 2001) (UK 16, USA 11, Germany 5, Italy 3, Canada/Japan/Norway 2, Denmark/Czech/Holland/Switzerland/Romania/Australia/Belgium 1). The second is that Higuchi himself has recently found a "killer ap" in the form of evolving analog intermediate frequency (IF) filters for cellular phones that NEC will manufacture at a rate of half a million per month! Higuchi spoke twice at the workshop, firstly as an invited speaker, and secondly as an regular speaker. In his invited speech, he gave examples of EH being applied by his group at ETL to industrial tasks, including work on a prosthetic hand, an autonomous robot, analog chips in cell phones, and femptosecond laser system alignment.


Session Speaker Highlights

There were some 30 session speaker slots. Due to space limitations, I review only three here.


Jordan Pollack -- "Throwaway Robots"

Pollack of Brandeis University, USA, presented his "Golem Project" (Genetically Organized Lifelike Electro Mechanics) which co-evolves simultaneously both robot bodies and their neural net controllers, or as he describes it, the "fully automated design of throwaway robots". He used an evolutionary algorithm to co-evolve 1) a neural net that was applied to motors to drive ball-and-socket jointed bars, and 2) the configuration of the bars to form a body, or robot. These bars were evolved to form a 3D "graph" of nodes (the joints) and lines (the bars). The linear motors made the lengths of the bars change, hence generating motion of the whole body. The fitness definition was the distance covered by the robot body in a given time. The elite individual after an EA run could then be built physically using a "3D fax" or "3D printing" technique called "rapid prototyping" in the commercial sector. This involves a machine that uses a temperature-controlled head to extrude thermoplastic material layer by layer to build arbitrary 3D shapes. This device would build the robot body with its bars and joints. The process was semi-automatic. The only task requiring human intervention was the insertion of the motors. What was new in Pollack's work relative to Karl Sims work, who similarly co-evolved bodies (interconnected blocks) and their neural controllers, was the semi-automated physical construction of the robots based on the evolved design. A colorful multimedia website presenting this work can be found at http://www.demo.cs.brandeis.edu/golem. Pollack's work was published in Nature [1].


Adrian Thompson -- "Evolutionary Nano-Electronics"

Thompson of Sussex University, U.K., is well known amongst evolvable hardware (E-Hard) researchers for his work on intrinsic EH. Thompson is now helping to pioneer the application of evolvable hardware techniques to the area of nanometer scale electronics or "nanoelectronics." This development is inevitable as Moore's law forces the scale of electronics to become ever smaller. Electronic processing speeds increase as the distance between components decreases, given the fixed and finite speed of light. Unfortunately, he was unable to attend the workshop, so he sent a video presentation instead. One of Thompson's main messages in his work over the last few years, is that EH can exploit the physics of the devices one evolves, for example, in his case, exploiting the inherent analog behavior of digital devices to perform a given task. In his "talk" (video) he tried to show how this "exploiting the physics" idea could be applied to the evolution of behavior in "single electronics" systems, i.e. those with very few electrons, e.g., quantum dots, SETs (single electron transistors), etc. The case study he chose was to evolve a "single electron NOR gate" in which he felt that "the particular thermal energies of the electrons are exploited." Hence hopefully, it may be possible to do in nanoelectronics what he did in microelectronics (FPGAs), i.e., to "explore beyond the scope of conventional design". Thompson had access to a software simulator of a single electron NOR gate circuit so he used this simulator as the basis of his investigation. The "gate" Thompson worked with consisted of an array of interconnected capacitors and tunneling "junctions." A junction consists of a thin layer of insulating material sandwiched between two slices of conducting material. Single electrons can "quantum tunnel" across the insulator junction.

A genetic algorithm was used to evolve arrays that consisted of a graph of nodes, arranged in a 7 by 4 matrix, whose links could contain a junction, a capacitor, a wire, or nothing. Links were only local, i.e., between neighboring nodes only. Numerical values for the capacitance of the capacitors and the tunnel resistance of the junctions were also evolved. The top row of nodes were supplied with a given voltage, and the bottom row of nodes kept at 0 volts. No components were allowed between the nodes in the top or bottom rows. The two input nodes and the output node were fixed. The fitness was defined to be proportional to how well a target output curve matched the actual. The target curve was a simple NOR function of two straightforward semi-square wave inputs. The evolution first took place in the simulation at 0 degrees Kelvin, and evolved well, but the fitness crashed if the temperature was increased by a mere 30 mK. Thompson then decided on an "incremental" or "stepwise" evolutionary approach to overcome the temperature sensitivity. Once the elite member of the population, of 30, reached a given fitness level, the temperature of simulation was raised by 10mK, and the resulting population at the lower temperature was used as the starting population for the higher temperature run. This procedure was followed until 340 mK. What he was then very surprised to discover was that not only would the fitness drop off as the temperature of simulation went above 340 mK, as would be expected, but that it also dropped off as the temperature decreased. Thompson interpreted this odd behavior to mean that the "circuit exploits or relies upon the particular thermal energies of the electrons at around 340 mK." This phenomenon may be a further example of the type of exploitation of the (nanoelectronic) physics that Thompson is so fascinated by. He is continuting his work on this phenomenon. Nano electronics people ought to study this work closely, as it opens up new avenues. In my view, this paper was the best at the workshop, and potentially the most significant for the future, which explains why I have devoted so much space to it.

I should note that Thompson is not the first to work on the theme of evolutionary nanoelectronics. Adrian Stoica et al. published a paper entitled "Evolutionary Design of Electronic Devices and Circuits" in 1999 [2]. Quoting from the abstract of that paper "This paper addresses the use of evolutionary algorithms in the design of electronic devices and circuits. In particular, the paper introduces the idea of evolutionary design of nanodevices, and illustrates it with the design of a resonant tunneling diode... ." Stoica and his colleagues at JPL also published a short paper called "Genetically Engineered Nanoelectronics" at the 1st NASA/DoD EH workshop in 1999, on page 247 of the proceedings.


Gary Fehr -- "Brain Building Machine, CBM"

Gary Fehr of Genobyte, Inc. of Boulder, Colorado, USA, develops software for the CAM-Brain Machine (CBM), The CBM is a piece of specialised evolvable hardware that evolves a 3D cellular automata-based neural network circuit module in a few seconds. The elite modules are downloaded into a gigabyte of RAM, one at a time, for 64000 modules, which are then interconnected according to the architectural decisions of human "BAs" (brain architects) to build artificial brains. Fehr showed off the capacities of the CBM. For example, it uses Xilinx's XC6264 FPGA chips (which have now been taken off the market because they were not popular with electronic engineers, and did not sell well) to update the billion 3D CA cells in the CBM at a rate of 130 billion a second. The CBM can execute a complete genetic algorithm run with a population of 100 modules over 100 generations in a second or so. There are maximum 1152 neurons per module, so with the 64000 modules that the CBM can handle, thats implies an artificial brain with the order of 100 million artificial neurons. Such a brain could be updated fast enough by the CBM to enable real-time control of robots. The CBM is the most powerful and one of the most significant examples of evolvable hardware on the planet. (See the Guinness Book of World Records, 2001, p126). Its design and construction was contracted to Michael Korkin, the president of Genobyte, by the de Garis' previous research lab in Kyoto, Japan (ATR) to implement de Garis' ideas on building artificial brains. There are four CBMs in the world: one in Japan at ATR, two in Belgium (one at Starlab, the author's present lab), and one at Genobyte in the U.S. Starlab obtained a $1M grant from the Brussels government in 2000 to build an artificial brain using its CBM.


Panel Discussion -- "Impact of Industry on E-Hard"

An industrial panel consisting of people from Virtual Computer Company (VCC), HP Labs, Triscend Inc, Xilinx, etc. discussed how industry could impact the EH field at four different levels: 1) user, 2) silicon level, 3) tools for EH, and 4) systems. The official title of the discussion was "The Future of Reconfigurable Computing Technologies: Industry Viewpoint." The HP Lab's representative said that current design methodologies don't scale well. For example, with HP Lab's microprocessor 200X, the gates are effectively free, the wires are expensive, design of symmetry is easy, and the design of irregularity is hard. He spoke about HP's Teramac project which consisted of a million gates operating at a megahertz with faulty components. One of the aims of the project was to create a functional system from imperfect components. The team found 220,000 defects, but they got their machine working nevertheless, a sort of genetic algorithm supercomputer.

The question was asked, "What can the (US) government do for EH?" The general answer, which I heartily agree with (see below in my general remarks), was the need for the government to fund the development of a large FPGA with definite dynamic reconfigurability characteristics for general use by the whole of the EH community. Such a chip could replace the Xilinx 6200 family of FPGAs which have traditionally been the intrinsic (in chip) EH chips of preference (see below).

The Triscend Inc.'s representative spoke mostly about "configurable systems on a chip" ("CSoC"s) mainly in a communications application context - for example his company's "E5" devices. (See http://www.triscend.com.) He felt that such chips accelerate the time to market, will have about 10 million gates, and create a market of about $50B in 10 years. He mentioned a list of companies doing the same kind of thing (Triscend, Atmel, Quick Logic, Chameleon, Altera, Lucent, LSI Logic, etc). His company's E5 chip is an eight-bit microcontroller, a byte-wide SRAM chip, with a processor and DMA controller on a single die. It can access any flip flop, and is fast. He made a remark that I really picked up on, namely - "The Triscend E5 has features useful for reconfiguration". E-Harders who are curious might like to check out their web site (and the others) to see if such "CSoC"s might be suitable for EH.

The Xilinx representatives (Delon Levi and Bill Carter) said that EH tools need to be created based on basic principles, for example, 1) people evolve first the functional FPGA nodes and then evolve the routing between them, in the context of CAs (cellular automata), NNs (neural networks), DSP (digital signal processors) filters, etc. 2) use main stream products so that the know-how of the experts can be used, 3) try to solve problems that engineers cant solve or that can be done more cheaply than paying an engineer, e.g. voice/video recognition etc. As for application areas, Levi suggested, pattern recognition, video, evolving the feature detectors, evolving DSP filters, cleaning up signals in noisy channels etc. Carter said that EH was not a big deal at Xilinx, that it was confined largely to academics. He felt that it was NASA that was driving the need for reconfigurability, for its long duration space voyages.

The VCC representative, John Schewel, with a colorful personality, asked "What I want is an artificial brain, but I get Kephera robots." "Is a digital soul possible?" He wants to incorporate the dynamics into computing architectures rather than simulating the dynamics. He wants to build a machine with billions of gates of reconfigurable logic that can be used in 2001.


Demonstration -- "CAM-Brain Machine CBM"

The conference featured one major demonstration, namely the hardware unveiling of the "CAM-Brain Machine (CBM)" mentioned above in Fehr's talk. Korkin and Fehr transported their own CBM to the workshop and showed it off to a crowd of onlookers in the lobby. Close to the machine was a large poster which read - "Genobyte, CAM-Brain Machine (CBM), A large scale evolvable hardware research platform; Cellular Automata Update Rate: 131 billion cells/second; Number of Supported Cellular Automata Cells: 893 million; Number of Supported Neurons (max., per neural module): 1152; Number of Supported Neural Modules: 64,640; Number of Supported Neurons (max. per brain): 74.5 million; Neural Module Chromosome Length: 91,000 bits; Number of FPGAs: 72 (Xilinx XC6264BG560); Number of FPGA Reconfigurable Function Units: 1,179,648; Phenotype/Genotype Memory: 1.18Gbytes; Power Consumption: 1.5KWatt (5V, 300A); Computational Power: 10,000 Pentium III 500 MHz PCs." Hopefully in the summer of 2001, de Garis and Genobyte will be able to show off what they have been able to build with the CBMs, namely an artificial brain architecture, or at least to show substantial progress along that route.


General Remarks

The first thing that surprised me about the workshop was that the definition of the word "hardware" had changed. As a father of the field in a sense, having had the original idea of considering the configuring bitstring of FPGAs as a genetic algorithm chromosome, I had the unconscious assumption that the term "evolvable hardware" meant "evolvable electronic hardware," but Pollack's paper, which I thought was one of the highlights of the workshop, showed that the workshop's organizers had generalized the definition to mean "evolvable matter." This seems to me to be a good thing, and opens up new avenues for research. For example, Thompson's evolvable nanoelectronics work makes the distinction between electronics and matter fuzzy, because at a small enough scale, e.g., nanometers, everything, whether electronics or matter, is made up of molecules.

My surprise at the redefinition of the term "evolvable hardware" was however somewhat unjustified, because in fact Stoica had alread said in the preface of the proceedings of the 1st NASA/DoD EH workshop in 1999 that "While this (electronics) is still the main vein of research, the semantic envelope has expanded to include various forms of hardware, from sensors to antennas to complete evolvable space systems... ."

Another remark which I think needs to be made was my impression that the workshop was "reinventing the wheel" to some extent. Some of the papers were definite "evolutionary computation" (EC) conference-type papers that would have been serious candidates for publication in a "pure EC" conference. Since these EH workshops use evolutionary computational techniques as the main tool to evolve its electronics (or hardware "matter") there is a case to be made in allowing EC type papers into an EH workshop, provided that they are not repititions of work that has already been done by the EC research community. There is already a large literature of EC work that has accumulated over the decades. My feeling was listening to some of the EC-type papers that they were just reinventions of earlier EC work that these EH researchers could have consulted in the EC journals and proceedings.

Some of the papers, especially towards the end of the workshop, were of questionable relevance. For example, the very last paper was on the use of a genetic algorithm to minimize the drag of fluid flow around a cylinder by placing actuators on the cylinder's surface. If such a paper is considered evolvable hardware, then so would many papers in the applications sections of EC conferences, thus diluting the meaning of the term "evolvable hardware" to almost nothing.

At a broader level, I was concerned that few remarks were made at the workshop at the lack of a replacement for the Xilinx 6400 FPGA family which has been the intrinsic EH workhorse for the field for several years. Xilinx's emphasis on its current "Virtex" FPGA family creates difficulties for the EH field. The most obvious one is that the detailed architecture of the Virtex is a Xilinx company secret, unlike the public disclosure of the XC6400 family architecture. EH researchers cannot write software for the evolution of the Virtex because they dont know the detailed circuitry. At the moment the only people who can do that are the EH researchers working inside Xilinx, lead by Delon Levi, who have in-house secret knowledge. This monopolistic situation is not healthy for the EH field. EH researchers can obtain the "JBits" software from Levi (Delon.Levi@xilinx.com) which acts as an interface between EH researchers who desire to evolve a Virtex chip and the secret Virtex internal architecture. What is needed is that the EH community develops its own evolvable chips that the field can use, and make them public, so that researchers all over the planet can contribute to their development, rather analogous to Linux, the "freeware" operating system. The problem however is cost. Xilinx spent millions of dollars developing their Virtex.

Fortunately, there are moves afoot to overcome this problem. Stoica and his colleagues at JPL have designed three generations of evolvable chips already. The 1st was fabricated in Oct 1998, the 2nd in Oct 2000, and the 3rd in March 2001. This work has been funded by DARPA and NASA, and the designs are public. The Stoica team does not support these chips in the sense of baby-sitting users, but it has given access to the chips via the internet to other organisations, e.g. NASA Ames and Natural Selection Inc. The intention of this government funding at JPL is that the chip designs will migrate towards industry. If industry takes up these designs, they are welcome.

Didier Keymeulen, a colleague of Adrian Stoica at JPL, feels that their analog reconfigurable chip is an alternative to the Xilinx XC6200 family of FPGAs. He says that one can "design your own chip on a laptop" due to the use of increasingly affordable design tools.


Acknowledgments

I would like to thank Adrian Stoica and Didier Keymeulen, both at JPL, for their suggested improvements and corrections of misconceptions in an earlier draft of this report.

References

1. H. Lipson and J. B. Pollack, "Automatic Design and Manufacture of Robotic Lifeforms", Nature 406, pp. 974-978, 2000.

2. A. Stoica, G. Klimeck, C. Salazar-Lazaro, D. Keymeulen, A. Thakoor, "Evolutionary Design of Electronic Devices and Circuits," Proceedings of the 1999 Congress on Evolutionary Computation, IEEE Press, Vol. 2, pp 1271-1278, 1999.