A DWM-Based Stack Architecture Implementation for Energy Harvesting Systems

Abstract

Energy harvesting systems tend to use non-volatile processors to conduct computation under intermittent power supplies. While previous implementations of non-volatile processors are based on register architectures, stack architecture, known for its simplicity and small footprint, seems to be a better fit for energy harvesting systems. In this work, Domain Wall Memory (DWM) is used to implement ZPU, the world’s smallest working CPU. Not only does DWM offer ultra-high density and SRAM-comparable access latency, but the sequential access structure of DWM also makes it well suited for a stack whose accesses display high temporal locality. As the performance and energy of DWM are determined by the number of shift operations performed to access the stack, this paper further reduces shift operations through novel data placement and micro-code transformation optimizations. The impact of compiler optimization techniques on the number of shift operations is also investigated so as to select the most effective optimizations for DWM-based stack machine. Experimental studies confirm the effectiveness of the proposed DWM-based stack architectures in improving the performance and energy-efficiency of energy harvesting systems.