1 citations · 1 across the 7 of their papers we have counts for
8 papers
CoRun: Padding is Simple and Efficient for Deterministic LLM Inference
Shiju Zhao, Jiacheng Yang, Qihang Chen +4
Despite fixed sampling parameters and random seeds, Large Language Model (LLM) inference exhibits output inconsistency, which undermines downstream tasks such as model evaluation a…
UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods
Yipeng Liu, Chang Liu, Si Shen +16
The deployment of Mixture-of-Experts (MoE) models on production high-bandwidth superpods, such as NVIDIA's NVL72/576 and Huawei's CloudMatrix384, introduces critical challenges bey…
AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending
Minyuan Zhou, Yuning Chen, Jiaqi Zheng +11
Operating large-scale anycast networks is challenging because client-to-site mappings often misalign with operator's expectation due to opaque inter-domain routing. We present AnyP…
You Need an Encoder for Native Position-Independent Caching
Shiju Zhao, Junhao Hu, Jiaqi Zheng +1
The Key-Value (KV) cache of Large Language Models (LLMs) is prefix-based, making it highly inefficient for processing contexts retrieved in arbitrary order. Position-Independent Ca…
MPIC: Position-Independent Multimodal Context Caching System for Efficient MLLM Serving
Shiju Zhao, Junhao Hu, Rongxiao Huang +2
The context caching technique is employed to accelerate the Multimodal Large Language Model (MLLM) inference by prevailing serving platforms currently. However, this approach merel…
CSR:Achieving 1 Bit Key-Value Cache via Sparse Representation
Hongxuan Zhang, Yao Zhao, Jiaqi Zheng +3
The emergence of long-context text applications utilizing large language models (LLMs) has presented significant scalability challenges, particularly in memory footprint. The linea…