This paper describes a 3D VLSI Chip for binary neural network classification applications. The 3D circuit includes three layers of MCM integrating 4 chips each making it a total of 12 chips integrated in a volume of (2 × 2 × 0.7)cm3. The architecture is scalable, and real-time binary neural network classifier systems could be built with one, two or all twelve chip solutions. Each basic chip includes an on-chip control unit for programming options of the neural network topology and precision. The system is modular and presents easy expansibility without requiring extra devices. Experimental test results showed that a full recall operation is obtained in less than 1.2μs for any topology with 4-bit or 8-bit precision while it is obtained in less than 2.2μs for any 16-bit precision. As a consequence the 3D chip is a very powerful reconfigurable and a multiprecision neural chip exhibiting a significant speed of 1.25 GCPS.
|Journal||Proceedings - IEEE International Symposium on Circuits and Systems|
|Publication status||Published - 2003|
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials