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HDA-MoE: Hybrid Parallelism and Dynamic, Adaptive Scheduling for Mixture-of-Experts with 3D Near-Memory Processing
Haochen Huang, Shuzhang Zhong, Shengxuan Qiu +8
Mixture-of-Experts (MoE) architectures have become a key technique for scaling Large Language Models (LLMs), enabling high model capacity with reduced computational cost. However,…
CODA: Algorithm-Hardware Co-design for Edge Video Diffusion via NMP-Enabled Compute-Cache Operator Disaggregation
Yuanpeng Zhang, YuXuan Wu, Yitong Xiao +6
Deploying Video Diffusion Models (VDMs) on edge devices is appealing for localized and privacy-preserving generation, but their iterative Transformer-based denoising remains too sl…
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…
Enabling Efficient Transaction Processing on CXL-Based Memory Sharing
Zhao Wang, Yiqi Chen, Cong Li +5
Transaction processing systems are the crux for modern data-center applications, yet current multi-node systems are slow due to network overheads. This paper advocates for Compute…