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NASPipe: high performance and reproducible pipeline parallel supernet training via causal synchronous parallelism.

S. Zhao, F. Li, X. Chen, T. Shen, L. Chen, S. Wang, N. Zhang, C. Li, and H. Cui. ASPLOS, page 374-387. ACM, (2022)

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Tianxiang Lu

Wan Shen

Wei Shen

Hong Shen

Other publications of authors with the same name

High-Performance Confidentiality-Preserving Blockchain via GPU-Accelerated Fully Homomorphic Encryption.R. Guan, T. Shen, S. Wang, G. Zhang, H. Cui, and J. Qi. CAiSE Workshops, volume 521 of Lecture Notes in Business Information Processing, page 25-36. Springer, (2024)AGRNav: Efficient and Energy-Saving Autonomous Navigation for Air-Ground Robots in Occlusion-Prone Environments.J. Wang, Z. Sun, X. Guan, T. Shen, Z. Zhang, T. Duan, D. Huang, S. Zhao, and H. Cui. ICRA, page 11133-11139. IEEE, (2024)NASPipe: high performance and reproducible pipeline parallel supernet training via causal synchronous parallelism.S. Zhao, F. Li, X. Chen, T. Shen, L. Chen, S. Wang, N. Zhang, C. Li, and H. Cui. ASPLOS, page 374-387. ACM, (2022)UPA: An Automated, Accurate and Efficient Differentially Private Big-Data Mining System.T. Li, J. Jiang, J. Qi, C. So, J. Ma, X. Chen, T. Shen, H. Cui, Y. Wang, and P. Wang. DSN, page 515-527. IEEE, (2020)MVSAS: Semantic-Aware Scheduling for Low Latency and High Precision in Wireless Multi-View Application.X. Guan, Z. Sun, S. Deng, S. Zhao, T. Shen, T. Li, Y. Wang, R. Wang, and H. Cui. ICPADS, page 266-273. IEEE, (2021)Coorp: Satisfying Low-Latency and High-Throughput Requirements of Wireless Network for Coordinated Robotic Learning.S. Deng, X. Guan, Z. Sun, S. Zhao, T. Shen, X. Chen, T. Duan, Y. Wang, J. Pan, Y. Wu and 2 other author(s). IEEE Internet Things J., 10 (3): 1946-1960 (February 2023)CRONUS: Fault-isolated, Secure and High-performance Heterogeneous Computing for Trusted Execution Environment.J. Jiang, J. Qi, T. Shen, X. Chen, S. Zhao, S. Wang, L. Chen, G. Zhang, X. Luo, and H. Cui. MICRO, page 124-143. IEEE, (2022)Bidl: A High-throughput, Low-latency Permissioned Blockchain Framework for Datacenter Networks.J. Qi, X. Chen, Y. Jiang, J. Jiang, T. Shen, S. Zhao, S. Wang, G. Zhang, L. Chen, M. Au and 1 other author(s). SOSP, page 18-34. ACM, (2021)DAENet: Making Strong Anonymity Scale in a Fully Decentralized Network.T. Shen, J. Jiang, Y. Jiang, X. Chen, J. Qi, S. Zhao, F. Zhang, X. Luo, and H. Cui. IEEE Trans. Dependable Secur. Comput., 19 (4): 2286-2303 (2022)SOTER: Guarding Black-box Inference for General Neural Networks at the Edge.T. Shen, J. Qi, J. Jiang, X. Wang, S. Wen, X. Chen, S. Zhao, S. Wang, L. Chen, X. Luo and 2 other author(s). USENIX ATC, page 723-738. USENIX Association, (2022)

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Disambiguation of "Shen, Tianxiang"

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NASPipe: high performance and reproducible pipeline parallel supernet training via causal synchronous parallelism.

Please choose a person to relate this publication to

Tianxiang Lu

Tianxiang Lu

Wan Shen

Wei Shen

Hong Shen

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Shen, Tianxiang"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML NASPipe: high performance and reproducible pipeline parallel supernet training via causal synchronous parallelism.

Please choose a person to relate this publication to

Tianxiang Lu

Tianxiang Lu

Wan Shen

Wei Shen

Hong Shen

Other publications of authors with the same name

Disambiguation

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URL
DOI
BibTeX
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APA
Chicago
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NASPipe: high performance and reproducible pipeline parallel supernet training via causal synchronous parallelism.