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Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.

X. Ma, G. Yuan, S. Lin, C. Ding, F. Yu, T. Liu, W. Wen, X. Chen, and Y. Wang. CoRR, (2019)

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Dr. Jianpei Geng University of Stuttgart

Yiwen Yuan University of Stuttgart

Other publications of authors with the same name

Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework.Y. Wang, C. Ding, Z. Li, G. Yuan, S. Liao, X. Ma, B. Yuan, X. Qian, J. Tang, Q. Qiu and 1 other author(s). AAAI, page 4235-4243. AAAI Press, (2018)Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs.C. Ding, A. Ren, G. Yuan, X. Ma, J. Li, N. Liu, B. Yuan, and Y. Wang. ACM Great Lakes Symposium on VLSI, page 353-358. ACM, (2018)A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation.G. Yuan, X. Ma, S. Lin, Z. Li, and C. Ding. CoRR, (2019)Non-structured DNN Weight Pruning Considered Harmful.Y. Wang, S. Ye, Z. He, X. Ma, L. Zhang, S. Lin, G. Yuan, S. Tan, Z. Li, D. Fan and 3 other author(s). CoRR, (2019)Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM.S. Lin, X. Ma, S. Ye, G. Yuan, K. Ma, and Y. Wang. CoRR, (2019)ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning.X. Ma, G. Yuan, S. Lin, Z. Li, H. Sun, and Y. Wang. CoRR, (2019)CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices.C. Ding, S. Liao, Y. Wang, Z. Li, N. Liu, Y. Zhuo, C. Wang, X. Qian, Y. Bai, G. Yuan and 6 other author(s). MICRO, page 395-408. ACM, (2017)Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.X. Ma, G. Yuan, S. Lin, C. Ding, F. Yu, T. Liu, W. Wen, X. Chen, and Y. Wang. CoRR, (2019)An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM.G. Yuan, X. Ma, C. Ding, S. Lin, T. Zhang, Z. Jalali, Y. Zhao, L. Jiang, S. Soundarajan, and Y. Wang. ISLPED, page 1-6. IEEE, (2019)An area and energy efficient design of domain-wall memory-based deep convolutional neural networks using stochastic computing.X. Ma, Y. Zhang, G. Yuan, A. Ren, Z. Li, J. Han, J. Hu, and Y. Wang. ISQED, page 314-321. IEEE, (2018)

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Disambiguation of "Yuan, Geng"

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Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.

Please choose a person to relate this publication to

Dr. Jianpei Geng University of Stuttgart

Yiwen Yuan University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Yuan, Geng"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.

Please choose a person to relate this publication to

Dr. Jianpei Geng University of Stuttgart

Yiwen Yuan University of Stuttgart

Other publications of authors with the same name

Disambiguation

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DOI
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Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.