High Throughput Neural Network based Embedded Streaming Multicore Processors - Tarek Taha: 2016 International Conference on Rebooting Computing
With power consumption becoming a critical processor design issue, specialized architectures for low power processing are becoming popular. Several studies have shown that neural networks can be used for signal processing and pattern recog-nition applications. This study examines the design of memris-tor based multicore neural processors that would be used pri-marily to process data directly from sensors. Additionally, we have examined the design of SRAM based neural processors for the same task. Full system evaluation of the multicore pro-cessors based on these specialized cores were performed taking I/O and routing circuits into consideration. The area and power benefits were compared with traditional multicore RISC pro-cessors. Our results show that the memristor based architec-tures can provide an energy efficiency between three and five orders of magnitude greater than that of RISC processors for the benchmarks examined.
Tarek Taha delivers a talk on multicore processors, at ICRC 2016.