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.
Redcim: Reconfigurable digital computing-in- memory processor with unified fp/int pipeline for cloud ai acceleration,
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A 28nm digital CIM accelerator for FP8 uses on-the-fly shift-aware bitwidth prediction, FIFO alignment, and scalable MACs to reach 20.4 TFLOPS/W and 2.8x better efficiency than prior work while supporting variable mantissa widths.
citing papers explorer
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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.
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Balancing FP8 Computation Accuracy and Efficiency on Digital CIM via Shift-Aware On-the-fly Aligned-Mantissa Bitwidth Prediction
A 28nm digital CIM accelerator for FP8 uses on-the-fly shift-aware bitwidth prediction, FIFO alignment, and scalable MACs to reach 20.4 TFLOPS/W and 2.8x better efficiency than prior work while supporting variable mantissa widths.