Mozart: Modularized and Efficient MoE Training on 3.5D Wafer-Scale Chiplet Architectures

NeurIPSSpotlight2025

Authors
Shuqing Luo, Ye Han, Pingzhi Li, Jiayin Qin, Jie Peng, Yang Katie Zhao, Yu Cao, Tianlong Chen
Venue
NeurIPS 2025
Track
Spotlight

TL;DR

Mixture-of-Experts (MoE) architecture offers enhanced efficiency for Large Language Models (LLMs) with modularized computation, yet its inherent sparsity poses significant hardware deployment challeng…

Opening excerpt from the authors’ abstract. source

Read the paper

Topics

large language model language model efficient sparsity llm

← All NeurIPS 2025 Spotlight papers · Browse the whole archive