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检索条件"机构=National Key Laboratory of Parallel and Distributed Computing School of Computer"
280 条 记 录,以下是1-10 订阅
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Training large-scale language models with limited GPU memory:a survey
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Frontiers of Information Technology & Electronic Engineering 2025年 第3期26卷 309-331页
作者: Yu TANG Linbo QIAO Lujia YIN Peng LIANG Ao SHEN Zhilin YANG Lizhi ZHANG Dongsheng LI National Key Laboratory of Parallel and Distributed Computing College of ComputerNational University of Defense TechnologyChangsha 410073China
Large-scale models have gained significant attention in a wide range of fields,such as computer vision and natural language processing,due to their effectiveness across various ***,a notable hurdle in training these l... 详细信息
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Funnel: An Efficient Sparse Attention Accelerator with Multi-Dataflow Fusion  22
Funnel: An Efficient Sparse Attention Accelerator with Multi...
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22nd IEEE International Symposium on parallel and distributed Processing with Applications, ISPA 2024
作者: Ma, Shenghong Xu, Jinwei Jiang, Jingfei Wang, Yaohua Li, Dongsheng National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing College of Computer Changsha China
The self-attention mechanism is the core component of Transformer, which provides a powerful ability to understand the sequence context. However, the self-attention mechanism also suffers from a large amount of redund... 详细信息
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Mbapp: Efficient Memory-Balanced Pipeline parallelism for Large Model Fine-Tuning on Commodity GPU Servers  24
Mbapp: Efficient Memory-Balanced Pipeline Parallelism for La...
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5th International Conference on computer Information and Big Data Applications, CIBDA 2024
作者: Liu, Yujie Lai, Zhiquan Li, Dongsheng National Key Laboratory of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410000 China
Large-scale models have demonstrated outstanding performance across various downstream tasks. Pipeline parallelism is essential for fine-tuning large models on commodity GPU servers, as it plays a crucial role in maki... 详细信息
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Area-NeRF: Area-based Neural Radiance Fields  2
Area-NeRF: Area-based Neural Radiance Fields
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2nd International Conference on Image Processing, computer Vision and Machine Learning, ICICML 2023
作者: Ye, Zonxin Li, Wenyu Qiao, Peng Dou, Yong National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing School of Computer Changsha China
Neural Radiance Field (NeRF) has received widespread attention for its photo-realistic novel view synthesis quality. Current methods mainly represent the scene based on point sampling of ray casting, ignoring the infl... 详细信息
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Highly parallelized Reinforcement Learning Training with Relaxed Assignment Dependencies  39
Highly Parallelized Reinforcement Learning Training with Rel...
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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025
作者: He, Zhouyu Qiao, Peng Li, Rongchun Dou, Yong Tan, Yusong College of Computer Science and Technology National University of Defense Technology China National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China
As the demands for superior agents grow, the training complexity of Deep Reinforcement Learning (DRL) becomes higher. Thus, accelerating training of DRL has become a major research focus. Dividing the DRL training pro... 详细信息
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Communication Analysis for Multidimensional parallel Training of Large-scale DNN Models  25
Communication Analysis for Multidimensional Parallel Trainin...
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25th IEEE International Conferences on High Performance computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023
作者: Lai, Zhiquan Hao, Yanqi Li, Shengwei Li, Dongsheng College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China
Multidimensional parallel training has been widely applied to train large-scale deep learning models like GPT-3. The efficiency of parameter communication among training devices/processes is often the performance bott... 详细信息
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Efficient Large Models Fine-tuning on Commodity Servers via Memory-balanced Pipeline parallelism  25
Efficient Large Models Fine-tuning on Commodity Servers via ...
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25th IEEE International Conferences on High Performance computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023
作者: Liu, Yujie Lai, Zhiquan Liu, Weijie Wang, Wei Li, Dongsheng College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China
Large models have achieved impressive performance in many downstream tasks. Using pipeline parallelism to fine-tune large models on commodity GPU servers is an important way to make the excellent performance of large ... 详细信息
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Rethinking the distributed DNN Training Cluster Design from the Cost-effectiveness View  25
Rethinking the Distributed DNN Training Cluster Design from ...
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25th IEEE International Conferences on High Performance computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023
作者: Lai, Zhiquan Liu, Yujie Wang, Wei Hao, Yanqi Li, Dongsheng College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China
As deep learning grows rapidly, model training heavily relies on parallel methods and there exist numerous cluster configurations. However, current preferences for parallel training focus on data centers, overlooking ... 详细信息
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Local-Adaptive Transformer for Multivariate Time Series Anomaly Detection and Diagnosis
Local-Adaptive Transformer for Multivariate Time Series Anom...
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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023
作者: Zhou, Xiaohui Wang, Yijie Xu, Hongzuo Liu, Mingyu Zhang, Ruyi College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China
Time series data are pervasive in varied real-world applications, and accurately identifying anomalies in time series is of great importance. Many current methods are insufficient to model long-term dependence, wherea...
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Deep Time Series Anomaly Detection with Local Temporal Pattern Learning
Deep Time Series Anomaly Detection with Local Temporal Patte...
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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025
作者: Li, Yizhou Wang, Yijie Xu, Hongzuo Zhou, Xiaohui National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Beijing100091 China
Self-supervised time series anomaly detection (TSAD) demonstrates remarkable performance improvement by extracting high-level data semantics through proxy tasks. Nonetheless, most existing self-supervised TSAD techniq... 详细信息
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