4 papers
AccelCIM: Systematic Dataflow Exploration for SRAM Compute-in-Memory Accelerator
Chenhao Xue, Yukun Wang, An Guo +11
SRAM-based compute-in-memory (CIM) offers high computational density and energy efficiency for deep neural network (DNN) accelerators, but its limited capacity causes on/off-chip d…
A Full-Stack Performance Evaluation Infrastructure for 3D-DRAM-based LLM Accelerators
Cong Li, Chenhao Xue, Yi Ren +11
Large language models (LLMs) exhibit memory-intensive behavior during decoding, making it a key bottleneck in LLM inference. To accelerate decoding execution, hybrid-bonding-based…
Hardware-Software Co-design for 3D-DRAM-based LLM Serving Accelerator
Cong Li, Yihan Yin, Chenhao Xue +7
Large language models (LLMs) have been widely deployed for online generative services, where numerous LLM instances jointly handle workloads with fluctuating request arrival rates…
AIM: Software and Hardware Co-design for Architecture-level IR-drop Mitigation in High-performance PIM
Yuanpeng Zhang, Xing Hu, Xi Chen +10
SRAM Processing-in-Memory (PIM) has emerged as the most promising implementation for high-performance PIM, delivering superior computing density, energy efficiency, and computation…