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A 28nm 1.07TFLOPS/mm2 Dynamic-Precision Training Processor with Online Dynamic Execution and Multi- Level-Aligned Block-FP Processing.

Y. Yang, R. Liu, C. Wei, W. Wang, W. Sun, J. Yue, H. Yang, and Y. Liu. CICC, page 1-2. IEEE, (2023)

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Liu Liu

Keetsin Liu

Ching Liu

Other publications of authors with the same name

GAAS: An Efficient Group Associated Architecture and Scheduler Module for Sparse CNN Accelerators.J. Wang, Z. Yuan, R. Liu, X. Feng, L. Du, H. Yang, and Y. Liu. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 39 (12): 5170-5182 (2020)14.2 A 65nm 24.7µJ/Frame 12.3mW Activation-Similarity-Aware Convolutional Neural Network Video Processor Using Hybrid Precision, Inter-Frame Data Reuse and Mixed-Bit-Width Difference-Frame Data Codec.Z. Yuan, Y. Yang, J. Yue, R. Liu, X. Feng, Z. Lin, X. Wu, X. Li, H. Yang, and Y. Liu. ISSCC, page 232-234. IEEE, (2020)An N-way group association architecture and sparse data group association load balancing algorithm for sparse CNN accelerators.J. Wang, Z. Yuan, R. Liu, H. Yang, and Y. Liu. ASP-DAC, page 329-334. ACM, (2019)Block-Wise Dynamic-Precision Neural Network Training Acceleration via Online Quantization Sensitivity Analytics.R. Liu, C. Wei, Y. Yang, W. Wang, H. Yang, and Y. Liu. CoRR, (2022)STICKER-T: An Energy-Efficient Neural Network Processor Using Block-Circulant Algorithm and Unified Frequency-Domain Acceleration.J. Yue, Y. Liu, R. Liu, W. Sun, Z. Yuan, Y. Tu, Y. Chen, A. Ren, Y. Wang, M. Chang and 2 other author(s). IEEE J. Solid State Circuits, 56 (6): 1936-1948 (2021)Block-Wise Dynamic-Precision Neural Network Training Acceleration via Online Quantization Sensitivity Analytics.R. Liu, C. Wei, Y. Yang, W. Wang, H. Yang, and Y. Liu. ASP-DAC, page 372-377. ACM, (2023)A 65-nm Energy-Efficient Interframe Data Reuse Neural Network Accelerator for Video Applications.Y. Yang, Y. Liu, Z. Yuan, W. Sun, R. Liu, J. Wang, J. Yue, X. Feng, Z. Yuan, X. Li and 1 other author(s). IEEE J. Solid State Circuits, 57 (8): 2574-2585 (2022)Entropy Solutions to the Dirichlet Problem for Nonlinear Diffusion Equations with Conservative Noise.K. Du, R. Liu, and Y. Wang. SIAM J. Math. Anal., 56 (1): 637-675 (February 2024)Toward Low-Bit Neural Network Training Accelerator by Dynamic Group Accumulation.Y. Yang, R. Liu, W. Sun, J. Yue, H. Yang, and Y. Liu. ASP-DAC, page 442-447. IEEE, (2022)A 28nm 1.07TFLOPS/mm2 Dynamic-Precision Training Processor with Online Dynamic Execution and Multi- Level-Aligned Block-FP Processing.Y. Yang, R. Liu, C. Wei, W. Wang, W. Sun, J. Yue, H. Yang, and Y. Liu. CICC, page 1-2. IEEE, (2023)

BibSonomy

Disambiguation of "Liu, Ruoyang"

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A 28nm 1.07TFLOPS/mm2 Dynamic-Precision Training Processor with Online Dynamic Execution and Multi- Level-Aligned Block-FP Processing.

Please choose a person to relate this publication to

Liu Liu

Liu Liu

Liu Liu

Keetsin Liu

Ching Liu

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Liu, Ruoyang"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A 28nm 1.07TFLOPS/mm2 Dynamic-Precision Training Processor with Online Dynamic Execution and Multi- Level-Aligned Block-FP Processing.

Please choose a person to relate this publication to

Liu Liu

Liu Liu

Liu Liu

Keetsin Liu

Ching Liu

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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MSOffice XML

A 28nm 1.07TFLOPS/mm2 Dynamic-Precision Training Processor with Online Dynamic Execution and Multi- Level-Aligned Block-FP Processing.