This paper presents a gate-block selection algorithm, which can synthesize a proper parameter extractor of the pre-computation-based content-addressable memory (PB-CAM) to enhance power efficiency for specific applications such as embedded systems, microprocessor and SOC, etc. Furthermore, a novel CAM cell design with single bit-line is proposed. The proposed CAM cell design requires only one heavy loading bit-line and merely is constructed with eight transistors. The whole PB-CAM design was described in Spice with TSMC 0.35 µm double-poly quadruple-metal CMOS process. We used Synopsys Nanosim to estimate power consumption. With a 128 words by 32 bits CAM size, the experimental results showed that our proposed PB-CAM effectively reduces 18.21% of comparison operations in the CAM and saves 16.75% in power reduction by synthesizing a proper parameter extractor of the PB-CAM compared with the 1's count PB-CAM. This implies that our proposed PB-CAM is more flexible and adaptive for specific applications.

Real-time collision detection is one of the most important intelligent processings in robotics. In collision detection, a large storage capasity is usually required to store the 3-dimensional information on the obstacles located in a workspace. Moreover, high-computational power is essential in not only coordinate transformation but also matching operation. In the proposed collision detection VLSI processor, the matching operation is drastically accelerated by using a content-addressable memory (CAM). A new obstacle representation based on a union of rectangular solids is also used to reduce the obstacle memory capacity, so that the collision detection can be performed by only magnitude comparison in parallel. Parallel architecture using several identical processor elements (PEs) is employed to perform the coordinate transformation at high speed, and each PE performs coordinate transformation at high speed based on the COordinate Rotation DIgital Computation (CORDIC) algorithms. When the 16 PEs and 144-kb CAM are used, the performance is evaluated to be 90 ms.