Energy efficiency limits of logic and memory

Abstract

We address practical limits of energy efficiency scaling for logic and memory. Scaling of logic will end with unreliable operation, making computers probabilistic as a side effect. The errors can be corrected or tolerated, but overhead will increase with further scaling. We address the tradeoff between scaling and error correction that yields minimum energy per operation, finding new error correction methods with energy consumption limits about 2× below current approaches. The maximum energy efficiency for memory depends on several other factors. Adiabatic and reversible methods applied to logic have promise, but overheads have precluded practical use. However, the regular array structure of memory arrays tends to reduce overhead and makes adiabatic memory a viable option. This paper reports an adiabatic memory that has been tested at about 85× improvement over standard designs for energy efficiency. Combining these approaches could set energy efficiency expectations for processor-in-memory computing systems.