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Chao Yang

9 papers hereh-index 332 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author6
  • last author1

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.DC4
  • cs.CV3
  • cs.IR1
  • cs.SD1
same name
  • Chao Yang — 60 papers, h 49
  • Chao Yang — 19 papers, h 21
  • Chao Yang — 12 papers, h 4
  • Chao Yang — 12 papers, h 5
  • Chao Yang — 11 papers, h 10
  • Chao Yang — 11 papers, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators
Showing cs.DCShow all

4 papers · 1 filter

cs.DC2026

Tropical: Enhancing SLO Attainment in Disaggregated LLM Serving via SLO-Aware Multiplexing

Jinming Ma, Jiefei Chen, Xiuhong Li +5

To guarantee service quality in transformer based large language model (LLM) serving, it is essential to meet the latency constraints of both the prefill phase (measured by Time-to…

cs.DC2026

W4A16 Mixed-Precision Matrix Multiplication on Decoupled Architecture: Kernel Design and Memory Bottleneck Analysis for Ascend NPUs

Yuanhong He, Peiyu Niu, Jun Chen +2

As Large Language Models (LLMs) scale, weight-only quantization (W4A16: 4-bit weights, 16-bit activations) becomes critical for reducing memory footprint with minimal accuracy loss…

cs.DC2025

A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training

Lijuan Jiang, Xingjian Qian, Zhenxiang Ma +4

Pipeline parallelism is an essential distributed parallelism method. Increasingly complex and diverse DNN models necessitate meticulously customized pipeline schedules for performa…

cs.DC2025

Zeppelin: Balancing Variable-length Workloads in Data Parallel Large Model Training

Chang Chen, Tiancheng Chen, Jiangfei Duan +7

Training large language models (LLMs) with increasingly long and varying sequence lengths introduces severe load imbalance challenges in large-scale data-parallel training. Recent…

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