5 papers
KVServe: Service-Aware KV Cache Compression for Communication-Efficient Disaggregated LLM Serving
Zedong Liu, Xinyang Ma, Dejun Luo +9
LLMs are widely adopted in production, pushing inference systems to their limits. Disaggregated LLM serving (e.g., PD separation and KV state disaggregation) improves scalability a…
CCL-D: A High-Precision Diagnostic System for Slow and Hang Anomalies in Large-Scale Model Training
Yida Gu, Fakang Wang, Jianhao Fu +17
As training scales grow, collective communication libraries (CCL) increasingly face anomalies arising from complex interactions among hardware, software, and environmental factors.…
ENEC: A Lossless AI Model Compression Method Enabling Fast Inference on Ascend NPUs
Jinwu Yang, Jiaan Wu, Zedong Liu +17
The rapid scaling of Large Language Models presents significant challenges for their deployment and inference, particularly on resource-constrained specialized AI hardware accelera…
ElasticMM: Efficient Multimodal LLMs Serving with Elastic Multimodal Parallelism
Zedong Liu, Shenggan Cheng, Guangming Tan +2
Multimodal large language models (MLLMs) extend LLMs to handle images, videos, and audio by incorporating feature extractors and projection modules. However, these additional compo…
SolarZip: An Efficient and Adaptive Compression Framework for Solar EUV Imaging Data
Zedong Liu, Song Tan, Alexander Warmuth +7
Context: With the advancement of solar physics research, next-generation solar space missions and ground-based telescopes face significant challenges in efficiently transmitting an…