NEON: Enabling Efficient Support for Nonlinear Operations in Resistive RAM-based Neural Network Accelerators. (arXiv:2211.05730v1 [cs.AR])

Resistive Random-Access Memory (RRAM) is well-suited to accelerate neural
network (NN) workloads as RRAM-based Processing-in-Memory (PIM) architectures
natively support highly-parallel multiply-accumulate (MAC) operations that form
the backbone of most NN workloads. Unfortunately, NN workloads such as
transformers require support for non-MAC operations (e.g., softmax) that RRAM
cannot provide natively. Consequently, state-of-the-art works either integrate
additional digital logic circuits to support the non-MAC operations or offload
the non-MAC operations to CPU/GPU, resulting in significant performance and
energy efficiency overheads due to …

arxiv enabling neon network neural network operations support