4 papers
Odin: Primitive-Level Synchronization for Distributed Point-Based Neural Rendering
Zhenxiang Ma, Zeyu He, Yuanzhen Zhou +6
Point-based neural rendering (PBNR) represents 3D scenes as explicit, trainable primitives and underpins high-quality reconstruction and emerging embodied AI and world-model pipeli…
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…
LandMarkSystem Technical Report
Zhenxiang Ma, Zhenyu Yang, Miao Tao +5
3D reconstruction is vital for applications in autonomous driving, virtual reality, augmented reality, and the metaverse. Recent advancements such as Neural Radiance Fields(NeRF) a…
GS-Cache: A GS-Cache Inference Framework for Large-scale Gaussian Splatting Models
Miao Tao, Yuanzhen Zhou, Haoran Xu +10
Rendering large-scale 3D Gaussian Splatting (3DGS) model faces significant challenges in achieving real-time, high-fidelity performance on consumer-grade devices. Fully realizing t…