Search Results for author: Yongjun He

Found 8 papers, 6 papers with code

Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters

1 code implementation10 Nov 2021 Xiangru Lian, Binhang Yuan, XueFeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen yang, Ce Zhang, Ji Liu

Specifically, in order to ensure both the training efficiency and the training accuracy, we design a novel hybrid training algorithm, where the embedding layer and the dense neural network are handled by different synchronization mechanisms; then we build a system called Persia (short for parallel recommendation training system with hybrid acceleration) to support this hybrid training algorithm.

Recommendation Systems

CoroBase: Coroutine-Oriented Main-Memory Database Engine

1 code implementation29 Oct 2020 Yongjun He, Jiacheng Lu, Tianzheng Wang

Lightweight coroutines ease the implementation of software prefetching to hide data stalls by overlapping computation and asynchronous data prefetching.

Databases

Decentralized Training of Foundation Models in Heterogeneous Environments

1 code implementation2 Jun 2022 Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Re, Ce Zhang

Our key technical contribution is a scheduling algorithm that allocates different computational "tasklets" in the training of foundation models to a group of decentralized GPU devices connected by a slow heterogeneous network.

Scheduling

Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees

1 code implementation2 Jun 2022 Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Re, Ce Zhang

Communication compression is a crucial technique for modern distributed learning systems to alleviate their communication bottlenecks over slower networks.

BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks

1 code implementation31 Aug 2023 Qiang Huang, Jiawei Jiang, Xi Susie Rao, Ce Zhang, Zhichao Han, Zitao Zhang, Xin Wang, Yongjun He, Quanqing Xu, Yang Zhao, Chuang Hu, Shuo Shang, Bo Du

To handle graphs in which features or connectivities are evolving over time, a series of temporal graph neural networks (TGNNs) have been proposed.

Link Prediction Node Classification

MACD R-CNN: An Abnormal Cell Nucleus Detection Method

no code implementations28 Jul 2020 Baoyan Ma, Jian Zhang, Feng Cao, Yongjun He

We design a fixed proposal module to generate fixed-sized feature maps of nuclei, which allows the new information of nucleus is used for classification.

Cell Detection Classification +4

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