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cs.AR2026
FusionCIM: Accelerating LLM Inference with Fusion-Driven Computing-in-Memory Architecture
Zihao Xuan, Jia Chen, Yewen Li +4
In this paper, we propose FusionCIM, an operator-fusion-driven compute-in-memory (CIM) accelerator architecture for efficient and scalable LLM inference, with three key innovations…
cs.AR2025
CompAir: Synergizing Complementary PIMs and In-Transit NoC Computation for Efficient LLM Acceleration
Hongyi Li, Songchen Ma, Huanyu Qu +5
The rapid advancement of Large Language Models (LLMs) has revolutionized various aspects of human life, yet their immense computational and energy demands pose significant challeng…
cs.AR2024
SynDCIM: A Performance-Aware Digital Computing-in-Memory Compiler with Multi-Spec-Oriented Subcircuit Synthesis
Kunming Shao, Fengshi Tian, Xiaomeng Wang +12
Digital Computing-in-Memory (DCIM) is an innovative technology that integrates multiply-accumulation (MAC) logic directly into memory arrays to enhance the performance of modern AI…