Fully Binarized, Parallel, RRAM-Based Computing Primitive for In-Memory Similarity Search

In this brief, we propose a fully-binarized XOR-based IMSS (In-Memory Similarity Search) using RRAM (Resistive Random Access Memory) arrays. XOR (Exclusive OR) operation is realized using 2T-2R bitcells arranged along the column in an array. This enables simultaneous match operation across multiple stored data vectors by performing analog column-wise XOR operation and summation to compute HD (Hamming Distance). The proposed scheme is experimentally validated on fabricated RRAM arrays. Full-system validation is performed through SPICE simulations using open source Skywater 130 nm CMOS PDK demonstrating energy of 17 fJ per XOR operation using the proposed bitcell with a full-system power dissipation of
$145~\mu \text{W}$
. Using projected estimations at advanced nodes (28 nm) energy savings of
$\approx 1.5\times $
compared to the state-of-the-art can be observed for a fixed workload. Application-level validation is performed on HSI (Hyper-Spectral Image) pixel classification task using the Salinas dataset demonstrating an accuracy of 91%.