2 citations · 3 across the 9 of their papers we have counts for
10 papers
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…
NanoCP: Taming Load Imbalance in Data-Expert Parallel Decoding under Variable-Length Workloads
Jiefei Chen, Binbin Lin, Jinming Ma +9
Modern serving systems for Mixture-of-Experts (MoE) models adopt hybrid data-expert parallelism: expert parallelism (EP) shards experts across GPUs to scale capacity, while data pa…
DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs
Size Zheng, Xuegui Zheng, Hanshi Sun +16
The scaling of large language models (LLMs) is currently bottlenecked by the rigidity of distributed programming. While high-performance libraries like CuBLAS and NCCL provide opti…
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
6Bit-Diffusion: Inference-Time Mixed-Precision Quantization for Video Diffusion Models
Rundong Su, Jintao Zhang, Zhihang Yuan +3
Diffusion transformers have demonstrated remarkable capabilities in generating videos. However, their practical deployment is severely constrained by high memory usage and computat…
MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design
Haojie Duanmu, Xiuhong Li, Zhihang Yuan +4
Mixture-of-Experts (MoE) models face deployment challenges due to their large parameter counts and computational demands. We explore quantization for MoE models and highlight two k…
Triton-distributed: Programming Overlapping Kernels on Distributed AI Systems with the Triton Compiler
Size Zheng, Wenlei Bao, Qi Hou +19
In this report, we propose Triton-distributed, an extension of existing Triton compiler, to overcome the programming challenges in distributed AI systems. Triton-distributed is the…
SKVQ: Sliding-window Key and Value Cache Quantization for Large Language Models
Haojie Duanmu, Zhihang Yuan, Xiuhong Li +3
Large language models (LLMs) can now handle longer sequences of tokens, enabling complex tasks like book understanding and generating lengthy novels. However, the key-value (KV) ca…
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving
Jiangfei Duan, Runyu Lu, Haojie Duanmu +5
Large language models (LLMs) have demonstrated remarkable performance, and organizations are racing to serve LLMs of varying sizes as endpoints for use-cases like chat, programming…
WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More
Yuxuan Yue, Zhihang Yuan, Haojie Duanmu +3
Large Language Models (LLMs) face significant deployment challenges due to their substantial memory requirements and the computational demands of auto-regressive text generation pr…