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EasyNUSC: An Efficient Heterogeneous Computing Framework for Non-uniform Sampling Two-Dimensional Convolution Applications.

Y. Lu, C. Yu, J. Xiao, H. Wang, H. Fu, S. Tang, B. Kang, and G. Zheng. ICA3PP, volume 13777 of Lecture Notes in Computer Science, page 707-721. Springer, (2022)

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Tang Tang

Fei Tang

Jian Tang

Junhua Tang

Xinhua Tang

Other publications of authors with the same name

Balancing Fairness and Efficiency for Cache Sharing in Semi-external Memory System.S. Tang, Q. Chai, C. Yu, Y. Li, and C. Sun. ICPP, page 13:1-13:11. ACM, (2020)HGP4CNN: an efficient parallelization framework for training convolutional neural networks on modern GPUs.H. Fu, S. Tang, B. He, C. Yu, and J. Sun. J. Supercomput., 77 (11): 12741-12770 (2021)An Adaptive Efficiency-Fairness Meta-Scheduler for Data-Intensive Computing.Z. Niu, S. Tang, and B. He. IEEE Trans. Serv. Comput., 12 (6): 865-879 (2019)Reinforcement Learning-Based Resource Partitioning for Improving Responsiveness in Cloud Gaming.Y. Li, X. Wang, H. Liu, L. Pu, S. Tang, G. Wang, and X. Liu. IEEE Trans. Computers, 71 (5): 1049-1062 (2022)Long-Term Fairness Scheduler for Pay-as-You-Use Cache Sharing Systems.Z. Zhou, S. Tang, H. Fu, W. Chang, C. Yu, C. Sun, Y. Li, and J. Xiao. ICA3PP, volume 13777 of Lecture Notes in Computer Science, page 330-350. Springer, (2022)Performance Modeling and Analysis for Critical Section Contention in Parallel Codes.J. Jin, Y. Zhang, S. Tang, and H. Fan. Trustcom/BigDataSE/ISPA, page 2139-2146. IEEE, (2016)HEGrid: A High Efficient Multi-Channel Radio Astronomical Data Gridding Framework in Heterogeneous Computing Environments.H. Wang, C. Yu, J. Xiao, S. Tang, M. Long, and M. Zhu. CoRR, (2022)Fairness-Efficiency Scheduling for Cloud Computing With Soft Fairness Guarantees.S. Tang, C. Yu, and Y. Li. IEEE Trans. Cloud Comput., 10 (3): 1806-1818 (2022)Correction to: An Efficient Retrieval Method for Astronomical Catalog Time Series Data.B. Li, C. Yu, X. Hu, J. Xiao, S. Tang, L. Li, and B. Ma. ICA3PP (1), volume 11334 of Lecture Notes in Computer Science, Springer, (2018)Deep Learning Assisted Resource Partitioning for Improving Performance on Commodity Servers.R. Chen, J. Wu, H. Shi, Y. Li, H. Yin, S. Tang, X. Liu, and G. Wang. PACT, page 153-154. ACM, (2020)

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Disambiguation of "Tang, Shanjiang"

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EasyNUSC: An Efficient Heterogeneous Computing Framework for Non-uniform Sampling Two-Dimensional Convolution Applications.

Please choose a person to relate this publication to

Tang Tang

Fei Tang

Jian Tang

Junhua Tang

Xinhua Tang

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tang, Shanjiang"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML EasyNUSC: An Efficient Heterogeneous Computing Framework for Non-uniform Sampling Two-Dimensional Convolution Applications.

Please choose a person to relate this publication to

Tang Tang

Fei Tang

Jian Tang

Junhua Tang

Xinhua Tang

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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EasyNUSC: An Efficient Heterogeneous Computing Framework for Non-uniform Sampling Two-Dimensional Convolution Applications.