Energy Efficient Associative Memory Based on Neural Cliques
Traditional memories use an address to index the stored data. Associative memories rely on a different principle: Part of previously stored data are used to retrieve the remaining part. They are widely used, for instance, in network routers for packet forwarding. A classical way to implement such memories is content addressable memory (CAM) Since its operation is fully parallel, the response is obtained in a single clock cycle. However, this comes at the cost of energy consumption. This brief proposes to use a recent type of neural networks as a novel way to implement associative memories. Owing to an efficient retrieval algorithm guided by the information being searched, they are a good candidate for low power associative memory. Compared to the CAM based system, the analog implementation of 12 kb neuro inspired memory designed for 65 nm CMOS technology offers 48% energy savings.
IEEE Transactions on Circuits and Systems II: Express Briefs