VPU-CIM: A 130nm, 33.98 TOPS/W RRAM based Compute-In-Memory Vector Co-Processor

Deep Learning inference on edge devices requires reduced memory load/store latency and low bit-precision computations. To address these challenges, we present VPU-CIM: a novel RRAM-based Compute-In-Memory (CIM) variable bit-precision vector co-processor. We introduce vector extensions to the RISC-V ISA and implement it as an in-memory compute unit with a unique data mapping strategy. The design is implemented using open-source Skywater 130nm PDK, with area estimates provided for TSMC 28nm and ASAP 7nm PDKs. Our design achieves an energy efficiency of 33.98 TOPS/W for a 4,4 (I, W) precision configuration. The results demonstrate the potential of RRAM-based vector computations in memory.