Підписатись
Qiang Wang
Qiang Wang
School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen
Підтверджена електронна адреса в hit.edu.cn - Домашня сторінка
Назва
Посилання
Посилання
Рік
Benchmarking state-of-the-art deep learning software tools
S Shi, Q Wang, P Xu, X Chu
2016 7th International Conference on Cloud Computing and Big Data (CCBD), 99-104, 2016
4672016
A Distributed Synchronous SGD Algorithm with Global Top- Sparsification for Low Bandwidth Networks
S Shi, Q Wang, K Zhao, Z Tang, Y Wang, X Huang, X Chu
IEEE ICDCS 2019, 2019
1762019
Performance modeling and evaluation of distributed deep learning frameworks on gpus
S Shi, Q Wang, X Chu
2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th …, 2018
1332018
A survey and measurement study of GPU DVFS on energy conservation
X Mei, Q Wang, X Chu
Digital Communications and Networks 3 (2), 89-100, 2017
1072017
Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training
Y Wang, Q Wang, S Shi, X He, Z Tang, K Zhao, X Chu
2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet …, 2020
102*2020
FADNet: A Fast and Accurate Network for Disparity Estimation
Q Wang, S Shi, S Zheng, K Zhao, X Chu
2020 International Conference on Robotics and Automation (ICRA), 2020
942020
The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study
Z Tang, Y Wang, Q Wang, X Chu
Proceedings of the Tenth ACM International Conference on Future Energy …, 2019
912019
A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification
S Shi, K Zhao, Q Wang, Z Tang, X Chu
IJCAI, 3411-3417, 2019
882019
GPGPU performance estimation with core and memory frequency scaling
Q Wang, X Chu
IEEE Transactions on Parallel and Distributed Systems 31 (12), 2865-2881, 2020
822020
Communication-efficient distributed deep learning with merged gradient sparsification on GPUs
S Shi, Q Wang, X Chu, B Li, Y Qin, R Liu, X Zhao
IEEE INFOCOM 2020-IEEE Conference on Computer Communications, 406-415, 2020
752020
IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation
Q Wang, S Zheng, Q Yan, F Deng, K Zhao, X Chu
IEEE International Conference on Multimedia and Expo (ICME) 2021, 2021
612021
Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees
S Shi, Z Tang, Q Wang, K Zhao, X Chu
The 24th European Conference on Artificial Intelligence, Santiago de …, 2020
332020
Energy-Aware Non-Preemptive Task Scheduling With Deadline Constraint in DVFS-Enabled Heterogeneous Clusters
Q Wang, X Mei, H Liu, YW Leung, Z Li, X Chu
IEEE Transactions on Parallel and Distributed Systems, 2022
31*2022
A dag model of synchronous stochastic gradient descent in distributed deep learning
S Shi, Q Wang, X Chu, B Li
2018 IEEE 24th International Conference on Parallel and Distributed Systems …, 2018
302018
G-CRS: GPU Accelerated Cauchy Reed-Solomon Coding
C Liu, Q Wang, X Chu, YW Leung
IEEE Transactions on Parallel and Distributed Systems 29 (7), 1484-1498, 2018
302018
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs
Z Tang, Y Wang, X He, L Zhang, X Pan, Q Wang, R Zeng, K Zhao, S Shi, ...
The 32nd International Joint Conference on Artificial Intelligence …, 2023
282023
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models
P Dong, L Li, Z Tang, X Liu, X Pan, Q Wang*, X Chu
International Conference on Machine Learning (ICML), 2024
262024
EDNet: Efficient Disparity Estimation with Cost Volume Combination and Attention-based Spatial Residual
S Zhang, Z Wang, Q Wang, J Zhang, G Wei, X Chu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
222021
Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format
S Shi, Q Wang, X Chu
2020 International Conference on Parallel and Distributed Systems, 2020
212020
Benchmarking and Dissecting the Nvidia Hopper GPU Architecture
W Luo, R Fan, Z Li, D Du, Q Wang*, X Chu
International Parallel and Distributed Processing Symposium (IPDPS), 2024
182024
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