A CIM-based hardware-software co-design in 65nm achieves up to 7.3x higher throughput and 49.59x better energy efficiency than NVIDIA Orin Nano for LLaMA3.2-1B, averaging 336 tokens/s and 173 tokens/J under INT4 across multiple SLMs.
An 8- mb dc-current-free binary-to-8b precision reram nonvolatile computing- in-memory macro using time-space-readout with 1286.4-21.6 tops/w for edge-ai devices,
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EdgeCIM: A Hardware-Software Co-Design for CIM-Based Acceleration of Small Language Models
A CIM-based hardware-software co-design in 65nm achieves up to 7.3x higher throughput and 49.59x better energy efficiency than NVIDIA Orin Nano for LLaMA3.2-1B, averaging 336 tokens/s and 173 tokens/J under INT4 across multiple SLMs.