Engineering Commons^™

Energy-Efficient Fpga-Based Parallel Quasi-Stochastic Computing, Ramu Seva, Prashanthi Metku, Minsu Choi

Electrical and Computer Engineering Faculty Research & Creative Works

The high performance of FPGA (Field Programmable Gate Array) in image processing applications is justified by its flexible reconfigurability, its inherent parallel nature and the availability of a large amount of internal memories. Lately, the Stochastic Computing (SC) paradigm has been found to be significantly advantageous in certain application domains including image processing because of its lower hardware complexity and power consumption. However, its viability is deemed to be limited due to its serial bitstream processing and excessive run-time requirement for convergence. To address these issues, a novel approach is proposed in this work where an energy-efficient implementation of SC …