Title :
A fully parallel 1-Mb CAM LSI for real-time pixel-parallel image processing
Author :
Ikenaga, Takeshi ; Ogura, Takeshi
Author_Institution :
NTT Lifestyle & Environ. Technol. Labs., Kanagawa, Japan
fDate :
4/1/2000 12:00:00 AM
Abstract :
For real-time image-processing applications, a highly parallel system that exploits parallelism is desirable. A content addressable memory (CAM), or an associative processor, that can perform various types of parallel processing with words as the basic unit is a promising component for creating such a system because of its suitability for LSI implementation. Conventional CAM LSI´s, however, have neither efficient function nor enough capacity for pixel-parallel processing. This paper describes a fully parallel 1-Mb CAM LSI. It has advanced functions for processing various pixel-parallel algorithms, such as mathematical morphology and discrete-time cellular neural networks. Moreover, since it has 16-K words, or processing elements (PEs), which can process 128/spl times/128 pixels in parallel, a board-sized pixel-parallel image-processing system can be implemented using several chips. A chip capable of operating at 56 MHz and 2.5 V was fabricated using 0.25-/spl mu/m full-custom CMOS technology with five aluminum layers. A total of 15.5 million transistors have been integrated into a 16.1/spl times/17.0 mm chip. Typical power dissipation is 0.25 W. Processing performance of various update and data transfer operations is 3-640 GOPS. This CAM LSI will make a significant contribution to the development of compact, high-performance image-processing systems.
Keywords :
CMOS memory circuits; associative processing; cellular neural nets; content-addressable storage; digital signal processing chips; image processing; image processing equipment; large scale integration; mathematical morphology; parallel architectures; parallel memories; real-time systems; 0.25 W; 0.25 micron; 1 Mbit; 128 pixel; 16384 pixel; 2.5 V; 56 MHz; SIMD; associative processor; content addressable memory; discrete-time CNN; discrete-time cellular neural networks; full-custom CMOS technology; fully parallel CAM LSI; highly parallel system; mathematical morphology; pixel-parallel algorithms; pixel-parallel image processing; real-time image-processing applications; Associative memory; CADCAM; CMOS technology; Cellular neural networks; Computer aided manufacturing; Large scale integration; Morphology; Parallel processing; Pixel; Real time systems;
Journal_Title :
Solid-State Circuits, IEEE Journal of