A 2.38 MCells/mm<sup>2</sup> 9.81 -350 TOPS/W RRAM Compute-in-Memory Macro in 40nm CMOS with Hybrid Offset/IOFF Cancellation and ICELL RBLSL Drop Mitigation
A dense compute-in-memory (CIM) macro using resistive random-access memory (RRAM) showing solutions to read channel mismatch, high I OFF , ADC offset, IR drop, and cell resistance variation is presented. By combining a hybrid analog/mixed-signal offset cancellation scheme and I<sub>CELL</sub>R<sub>BLSL</sub> drop mitigation with a low cell bias target voltage, the proposed macro demonstrates robust operation (post-ECC bit error rate (BER )<5×10<sup>−8</sup> for 8WL CIM) while maintaining an effective cell density 1.03 – 33.1× higher than prior art and achieving 1.74 – 13.35× improved average MAC efficiency relative to the previous highest-density RRAM CIM macro. authors: S. D. Spetalnick, M. Chang, S. Konno, B. Crafton, A. S. Lele, W.-S. Khwa, Y.-D. Chih, M.-F. Chang, A. Raychowdhury
Artificial Intelligence
Artificial Intelligence
Since the last decade, we have been witnessing a steep rise of Artificial Intelligence (AI) as an alternative computing paradigm. Although the idea has been around since 1950s, AI needed progress in algorithms, capable hardware, and sufficiently large training data to become a practical and powerful tool. Progress in computing hardware has been a key ingredient for the AI renaissance and will remain increasingly critical to realize future AI applications.
We are particularly well-positioned to supply the most advanced AI hardware to our customers thanks to our leading-edge logic, memory, and packaging technologies. We have established a research pipeline for technology to enable leading-edge AI devices, circuits, and systems for decades to come. Near- and in-memory computing, embedded non-volatile memory technologies, 3D integration, and error-resilient computing are amongst our specific AI hardware research areas. Our in-house research is complemented by strong academic and governmental partnerships, which allow us to interact with and influence leading AI researchers around the world.
