| Autor: |
Sandeep Kaur Kingra, Vivek Parmar, Deepak Verma, Alessandro Bricalli, Giuseppe Piccolboni, Gabriel Molas, Amir Regev, Manan Suri |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Popis: |
In this work, 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 $\mu$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 90%. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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