papers

Publications (7)

cs.DC2026

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…

cs.DC2026

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.…

cs.DC2026

A Fully GPU-Accelerated Framework for High-Performance Configuration Interaction Selection with Neural Network Quantum States

Daran Sun, Bowen Kan, Haoquan Long +13

AI-driven methods have demonstrated considerable success in tackling the central challenge of accurately solving the Schrödinger equation for complex many-body systems. Among neur…

astro-ph.IM2025

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…

cs.AR2026

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…

cs.DC2024

Overcoming Memory Constraints in Quantum Circuit Simulation with a High-Fidelity Compression Framework

Boyuan Zhang, Bo Fang, Fanjiang Ye +4

Full-state quantum circuit simulation requires exponentially increased memory size to store the state vector as the number of qubits scales, presenting significant limitations in c…

cs.DC2025

TSUE: A Two-Stage Data Update Method for an Erasure Coded Cluster File System

Zheng Wei, Jing Xing, Yida Gu +4

Compared to replication-based storage systems, erasure-coded storage incurs significantly higher overhead during data updates. To address this issue, various parity logging methods…