Designers and users of computer systems have long been aware of the fact that inclusion of some kind of content-addressable or "associative" functions in the storage and retrieval mechanisms would allow a more effective and straightforward organization of data than with the usual addressed memories, with the result that the computing power would be significantly increased. However, although the basic principles of content-addressing have been known for over twenty years, the hardware content-addressable memories (CAMs) have found their way only to special roles such as small buffer memories and con trol units. This situation now seems to be changing: Because of the develop ment of new technologies such as very-large-scale integration of semiconduc tor circuits, charge-coupled devices, magnetic-bubble memories, and certain devices based on quantum-mechanical effects, an increasing amount of active searching functions can be transferred to memory units. The prices of the more complex memory components which earlier were too high to allow the application of these principles to mass memories will be reduced to a fraction of the to tal system costs, and this will certainly have a significant impact on the new computer architectures. In order to advance the new memory principles and technologies, more in formation ought to be made accessible to a common user.

The content-addressable memories (CAMs) have major applications in developing areas of artificial intelligence and image processing. This work involves researching, designing, and implementing a high performance, high density CAM. The design, fabrication, and test of this all-parallel AFIT CAM is discussed. The AFIT CAM stores 2K bits of information and fits in 64 pin dual-in-line package. It was fabricated using a 3 micron CMOS technology with 2-layer metals. The AFIT CAM supports four types of comparisons directly on the chip. These are equal, not-equal, greater-than-or-equal, and less-than. In addition, it has DUMP and Parallel Write operations to aid artificial intelligence and image processing applications. The AFIT CAM has a total of 78,000 devices and achieves a density of 1,073 devices per sq. mm. The memory access time for reading and writing are only 22 ns and 20 ns respectively. The CAM chip computes 800 million magnitude comparisons or 3.2 billion equality comparisons per second. The cif file has been resubmitted to the manufacturer for fabrication due to a short circuit which was caused by over bloated second metal lines. A second version of the AFIT CAM cell has been redesigned and nets a 25% reduction in size. (Author).

With the advance of semiconductors and ubiquitous computing, the use of system-on-a-chip (SoC) has become an essential technique to reduce product cost. With this progress and continuous reduction of feature sizes, and the development of very large-scale integration (VLSI) circuits, addressing the harder problems requires fundamental understanding