A Synthesis Methodology for Application-Specific Logic-in-Memory Designs

For deeply scaled digital integrated systems, the power required for transporting data between memory and logic can exceed the power needed for computation, thereby limiting the efficacy of synthesizing logic and compiling memory independently. Logic-in-Memory (LiM) architectures address this challenge by embedding logic within the memory block to perform basic operations on data locally for specific functions. While custom smart memories have been successfully constructed for various applications, a fully automated LiM synthesis flow enables architectural exploration that has heretofore not been possible. In this paper we present a tool and design methodology for LiM physical synthesis that performs co-design of algorithms and architectures to explore system level trade-offs. The resulting layouts and timing models can be incorporated within any physical synthesis tool. Silicon results shown in this paper demonstrate a 250x performance improvement and 310x energy savings for a data-intensive application example.