Talk Abstract Gate Array, Configure Thyself Nicholas J. Macias, Cell Matrix Corporation talk given at The Conference on High Speed Computing, Salishan Lodge, Gleneden, Oregon, U.S.A., April 26 2001. Conference sponsored by Los Alamos, Lawrence Livermore, and Sandia National Laboratories. Reconfigurable hardware brings the flexibility of software to the hardware domain, by allowing the behavior of physically-fixed hardware to be modified by a post-manufacturing configuration step. This allows the costly ASIC design and fabrication steps to be performed once, with inexpensive software configuration subsequently used to tailor the device to a particular need.      Unfortunately, traditional reconfigurable devices (FPGAs) share a common characteristic of being externally configured, meaning that configuration information is generated and transmitted to the device by something outside the device itself. This creates a configuration bottleneck, leading to an increase in configuration time as the size of the FPGA grows. Furthermore, configuration operations based on the current state of the FPGA's circuits (for example, an architecture-tuning system or a run-time fault handling system) require information about the FPGA's state to be transmitted to this external controller, creating additional bottlenecks. These bottlenecks grow from minor annoyances to serious showstoppers when considering Avogadro-scale (10^23 gates) machines.      In this talk, the speaker will describe a new type of self-configurable device called the Cell Matrix ™ which, unlike FPGAs, possesses an intrinsic and very natural mechanism for configuring its own circuitry. This and other architectural features of the Cell Matrix will be described, along with the benefits they present, including rapid autonomous configuration, fault tolerance, ease of manufacture, and infinite scalability. The speaker will then describe applications of the Cell Matrix to evolvable hardware, including the construction of autonomous, massively-parallel genetic algorithms. The talk will conclude with a discussion of how the Cell Matrix might be applied to the field of artificial brain building, by employing the architecture to implement massively-parallel, self-evolving neural networks.