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2020 – today
- 2023
[j43]Bo Zhang
, Shihui Yin, Minkyu Kim, Jyotishman Saikia, Soonwan Kwon, Sungmeen Myung, Hyunsoo Kim, Sang Joon Kim, Jae-Sun Seo, Mingoo Seok:
PIMCA: A Programmable In-Memory Computing Accelerator for Energy-Efficient DNN Inference. IEEE J. Solid State Circuits 58(5): 1436-1449 (2023)- [c94]Vasundhara Damodaran, Ziyu Liu, Jae-Sun Seo, Arindam Sanyal:
A 138-TOPS/W Delta-Sigma Modulator-Based Variable- Resolution Activation in-Memory Computing Macro. CICC 2023: 1-2 - [c93]Injune Yeo, Dong-Woo Jee, Jae-Sun Seo:
A 92 F2 / bit Physically Unclonable Function Exploiting Channel Charge Injection and Mismatch Accumulation. CICC 2023: 1-2 - [i14]Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi:
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR abs/2304.04640 (2023) - 2022
- [j42]Sai Kiran Cherupally, Jian Meng, Adnan Siraj Rakin, Shihui Yin, Mingoo Seok, Deliang Fan, Jae-Sun Seo:
Improving DNN Hardware Accuracy by In-Memory Computing Noise Injection. IEEE Des. Test 39(4): 71-80 (2022) - [j41]Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti, Jae-Sun Seo, Ümit Y. Ogras, Yu Cao:
Impact of On-chip Interconnect on In-memory Acceleration of Deep Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 18(2): 34:1-34:22 (2022) - [j40]Jian Meng, Wonbo Shim, Li Yang, Injune Yeo, Deliang Fan, Shimeng Yu, Jae-sun Seo:
Temperature-Resilient RRAM-Based In-Memory Computing for DNN Inference. IEEE Micro 42(1): 89-98 (2022) - [j39]Gokul Krishnan, Zhenyu Wang, Injune Yeo, Li Yang, Jian Meng, Maximilian Liehr, Rajiv V. Joshi, Nathaniel C. Cady, Deliang Fan, Jae-Sun Seo, Yu Cao:
Hybrid RRAM/SRAM in-Memory Computing for Robust DNN Acceleration. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(11): 4241-4252 (2022) - [c92]Ahmed Hasssan, Jian Meng, Yu Cao, Jae-sun Seo:
Spatial-temporal Data Compression of Dynamic Vision Sensor Output with High Pixel-level Saliency using Low-precision Sparse Autoencoder. IEEECONF 2022: 344-348 - [c91]Fan Zhang, Li Yang, Jian Meng, Yu Kevin Cao, Jae-sun Seo, Deliang Fan:
XBM: A Crossbar Column-wise Binary Mask Learning Method for Efficient Multiple Task Adaption. ASP-DAC 2022: 610-615 - [c90]Bo Zhang, Jyotishman Saikia, Jian Meng, Dewei Wang, Soonwan Kwon, Sungmeen Myung, Hyunsoo Kim, Sang Joon Kim, Jae-sun Seo, Mingoo Seok:
A 177 TOPS/W, Capacitor-based In-Memory Computing SRAM Macro with Stepwise-Charging/Discharging DACs and Sparsity-Optimized Bitcells for 4-Bit Deep Convolutional Neural Networks. CICC 2022: 1-2 - [c89]Jian Meng, Li Yang, Jinwoo Shin, Deliang Fan, Jae-Sun Seo:
Contrastive Dual Gating: Learning Sparse Features With Contrastive Learning. CVPR 2022: 12247-12255 - [c88]Fan Zhang, Li Yang, Jian Meng, Jae-sun Seo, Yu Kevin Cao, Deliang Fan:
XMA: a crossbar-aware multi-task adaption framework via shift-based mask learning method. DAC 2022: 271-276 - [c87]Fan Zhang, Li Yang, Jian Meng, Jae-Sun Seo, Yu Cao, Deliang Fan:
XST: A Crossbar Column-wise Sparse Training for Efficient Continual Learning. DATE 2022: 48-51 - [c86]Shreyas Kolala Venkataramanaiah, Jian Meng, Han-Sok Suh, Injune Yeo, Jyotishman Saikia, Sai Kiran Cherupally, Yichi Zhang, Zhiru Zhang, Jae-sun Seo:
A 28nm 8-bit Floating-Point Tensor Core based CNN Training Processor with Dynamic Activation/Weight Sparsification. ESSCIRC 2022: 89-92 - [c85]Amitesh Sridharan, Shaahin Angizi, Sai Kiran Cherupally, Fan Zhang, Jae-Sun Seo, Deliang Fan:
A 1.23-GHz 16-kb Programmable and Generic Processing-in-SRAM Accelerator in 65nm. ESSCIRC 2022: 153-156 - [c84]Gokul Krishnan, A. Alper Goksoy, Sumit K. Mandal, Zhenyu Wang, Chaitali Chakrabarti, Jae-sun Seo, Ümit Y. Ogras, Yu Cao:
Big-Little Chiplets for In-Memory Acceleration of DNNs: A Scalable Heterogeneous Architecture. ICCAD 2022: 8:1-8:9 - [c83]Jian Meng, Injune Yeo, Wonbo Shim, Li Yang, Deliang Fan, Shimeng Yu, Jae-Sun Seo:
Sparse and Robust RRAM-based Efficient In-memory Computing for DNN Inference. IRPS 2022: 3 - [c82]Li Yang, Jian Meng, Jae-sun Seo, Deliang Fan:
Get More at Once: Alternating Sparse Training with Gradient Correction. NeurIPS 2022 - 2021
- [j38]Tinoosh Mohsenin, Inna Partin-Vaisband, Houman Homayoun, Jae-Sun Seo, Xin Zhang:
Guest Editorial Cross-Layer Designs, Methodologies, and Systems to Enable Micro AI for On-Device Intelligence. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 527-531 (2021) - [j37]Arnab Neelim Mazumder, Jian Meng, Hasib-Al Rashid, Utteja Kallakuri, Xin Zhang, Jae-Sun Seo, Tinoosh Mohsenin:
A Survey on the Optimization of Neural Network Accelerators for Micro-AI On-Device Inference. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 532-547 (2021) - [j36]Minkyu Kim, Jae-Sun Seo:
An Energy-Efficient Deep Convolutional Neural Network Accelerator Featuring Conditional Computing and Low External Memory Access. IEEE J. Solid State Circuits 56(3): 803-813 (2021) - [j35]Jian Meng, Li Yang, Xiaochen Peng, Shimeng Yu, Deliang Fan, Jae-Sun Seo:
Structured Pruning of RRAM Crossbars for Efficient In-Memory Computing Acceleration of Deep Neural Networks. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1576-1580 (2021) - [j34]Gokul Krishnan, Sumit K. Mandal, Manvitha Pannala, Chaitali Chakrabarti, Jae-Sun Seo, Ümit Y. Ogras, Yu Cao:
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks. ACM Trans. Embed. Comput. Syst. 20(5s): 68:1-68:24 (2021) - [c81]Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti, Jae-Sun Seo, Ümit Y. Ogras, Yu Cao:
System-Level Benchmarking of Chiplet-based IMC Architectures for Deep Neural Network Acceleration. ASICON 2021: 1-4 - [c80]Sai Kiran Cherupally, Adnan Siraj Rakin, Shihui Yin, Mingoo Seok, Deliang Fan, Jae-sun Seo:
Leveraging Noise and Aggressive Quantization of In-Memory Computing for Robust DNN Hardware Against Adversarial Input and Weight Attacks. DAC 2021: 559-564 - [c79]Jyotishman Saikia, Shihui Yin, Sai Kiran Cherupally, Bo Zhang, Jian Meng, Mingoo Seok, Jae-Sun Seo:
Modeling and Optimization of SRAM-based In-Memory Computing Hardware Design. DATE 2021: 942-947 - [c78]Jian Meng, Shreyas Kolala Venkataramanaiah, Chuteng Zhou, Patrick Hansen, Paul N. Whatmough, Jae-sun Seo:
FixyFPGA: Efficient FPGA Accelerator for Deep Neural Networks with High Element-Wise Sparsity and without External Memory Access. FPL 2021: 9-16 - [c77]Anupreetham Anupreetham, Mohamed Ibrahim, Mathew Hall, Andrew Boutros, Ajay Kuzhively, Abinash Mohanty, Eriko Nurvitadhi, Vaughn Betz, Yu Cao, Jae-sun Seo:
End-to-End FPGA-based Object Detection Using Pipelined CNN and Non-Maximum Suppression. FPL 2021: 76-82 - [c76]Han-Sok Suh, Jian Meng, Ty Nguyen, Shreyas K. Venkataramanaiah, Vijay Kumar, Yu Cao, Jae-sun Seo:
Algorithm-Hardware Co-Optimization for Energy-Efficient Drone Detection on Resource-Constrained FPGA. FPT 2021: 1-9 - [c75]Wangxin He, Wonbo Shim, Shihui Yin, Xiaoyu Sun, Deliang Fan, Shimeng Yu, Jae-sun Seo:
Characterization and Mitigation of Relaxation Effects on Multi-level RRAM based In-Memory Computing. IRPS 2021: 1-7 - [c74]Wonbo Shim, Jian Meng, Xiaochen Peng, Jae-sun Seo, Shimeng Yu:
Impact of Multilevel Retention Characteristics on RRAM based DNN Inference Engine. IRPS 2021: 1-4 - [c73]Vinay Joshi, Wangxin He, Jae-sun Seo, Bipin Rajendran:
Hybrid In-Memory Computing Architecture for the Training of Deep Neural Networks. ISCAS 2021: 1-5 - [c72]Shihui Yin, Bo Zhang, Minkyu Kim, Jyotishman Saikia, Soonwan Kwon, Sungmeen Myung, Hyunsoo Kim, Sang Joon Kim, Mingoo Seok, Jae-sun Seo:
PIMCA: A 3.4-Mb Programmable In-Memory Computing Accelerator in 28nm for On-Chip DNN Inference. VLSI Circuits 2021: 1-2 - [i13]Vinay Joshi, Wangxin He, Jae-sun Seo, Bipin Rajendran:
Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks. CoRR abs/2102.05271 (2021) - [i12]Adnan Siraj Rakin, Li Yang, Jingtao Li, Fan Yao, Chaitali Chakrabarti, Yu Cao, Jae-sun Seo, Deliang Fan:
RA-BNN: Constructing Robust & Accurate Binary Neural Network to Simultaneously Defend Adversarial Bit-Flip Attack and Improve Accuracy. CoRR abs/2103.13813 (2021) - [i11]Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti, Jae-sun Seo, Ümit Y. Ogras, Yu Cao:
Impact of On-Chip Interconnect on In-Memory Acceleration of Deep Neural Networks. CoRR abs/2107.02358 (2021) - [i10]Gokul Krishnan, Sumit K. Mandal, Manvitha Pannala, Chaitali Chakrabarti, Jae-sun Seo, Ümit Y. Ogras, Yu Cao:
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks. CoRR abs/2108.08903 (2021) - 2020
- [j33]Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti, Jae-sun Seo, Ümit Y. Ogras, Yu Cao:
Interconnect-Aware Area and Energy Optimization for In-Memory Acceleration of DNNs. IEEE Des. Test 37(6): 79-87 (2020) - [j32]Sumit K. Mandal, Gokul Krishnan, Chaitali Chakrabarti, Jae-Sun Seo, Yu Cao, Ümit Y. Ogras:
A Latency-Optimized Reconfigurable NoC for In-Memory Acceleration of DNNs. IEEE J. Emerg. Sel. Topics Circuits Syst. 10(3): 362-375 (2020) - [j31]Shihui Yin, Zhewei Jiang, Jae-Sun Seo, Mingoo Seok:
XNOR-SRAM: In-Memory Computing SRAM Macro for Binary/Ternary Deep Neural Networks. IEEE J. Solid State Circuits 55(6): 1733-1743 (2020) - [j30]Deepak Kadetotad, Shihui Yin, Visar Berisha, Chaitali Chakrabarti, Jae-sun Seo:
An 8.93 TOPS/W LSTM Recurrent Neural Network Accelerator Featuring Hierarchical Coarse-Grain Sparsity for On-Device Speech Recognition. IEEE J. Solid State Circuits 55(7): 1877-1887 (2020) - [j29]Zhewei Jiang, Shihui Yin, Jae-Sun Seo, Mingoo Seok:
C3SRAM: An In-Memory-Computing SRAM Macro Based on Robust Capacitive Coupling Computing Mechanism. IEEE J. Solid State Circuits 55(7): 1888-1897 (2020) - [j28]Sai Kiran Cherupally, Shihui Yin, Deepak Kadetotad, Chisung Bae, Sang Joon Kim, Jae-sun Seo:
A Smart Hardware Security Engine Combining Entropy Sources of ECG, HRV, and SRAM PUF for Authentication and Secret Key Generation. IEEE J. Solid State Circuits 55(10): 2680-2690 (2020) - [j27]Sai Kiran Cherupally, Shihui Yin, Deepak Kadetotad, Gaurav Srivastava, Chisung Bae, Sang Joon Kim, Jae-sun Seo:
ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression. IEEE Trans. Biomed. Circuits Syst. 14(2): 198-208 (2020) - [j26]Yufei Ma, Yu Cao, Sarma B. K. Vrudhula, Jae-Sun Seo:
Automatic Compilation of Diverse CNNs Onto High-Performance FPGA Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(2): 424-437 (2020) - [j25]Yufei Ma, Yu Cao, Sarma B. K. Vrudhula, Jae-Sun Seo:
Performance Modeling for CNN Inference Accelerators on FPGA. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(4): 843-856 (2020) - [j24]Shihui Yin, Zhewei Jiang, Minkyu Kim, Tushar Gupta, Mingoo Seok, Jae-Sun Seo:
Vesti: Energy-Efficient In-Memory Computing Accelerator for Deep Neural Networks. IEEE Trans. Very Large Scale Integr. Syst. 28(1): 48-61 (2020) - [c71]Minkyu Kim, Jae-Sun Seo:
Deep Convolutional Neural Network Accelerator Featuring Conditional Computing and Low External Memory Access. CICC 2020: 1-4 - [c70]Xiaocong Du, Zheng Li, Jae-sun Seo, Frank Liu, Yu Cao:
Noise-based Selection of Robust Inherited Model for Accurate Continual Learning. CVPR Workshops 2020: 983-988 - [c69]Shruti R. Kulkarni, Shihui Yin, Jae-sun Seo, Bipin Rajendran:
An On-Chip Learning Accelerator for Spiking Neural Networks using STT-RAM Crossbar Arrays. DATE 2020: 1019-1024 - [c68]Shreyas K. Venkataramanaiah, Han-Sok Suh, Shihui Yin, Eriko Nurvitadhi, Aravind Dasu, Yu Cao, Jae-Sun Seo:
FPGA-based Low-Batch Training Accelerator for Modern CNNs Featuring High Bandwidth Memory. ICCAD 2020: 74:1-74:8 - [c67]Shreyas Kolala Venkataramanaiah, Xiaocong Du, Zheng Li, Shihui Yin, Yu Cao, Jae-sun Seo:
Efficient and Modularized Training on FPGA for Real-time Applications. IJCAI 2020: 5237-5239 - [c66]Xiaocong Du, Shreyas Kolala Venkataramanaiah, Zheng Li, Jae-sun Seo, Frank Liu, Yu Cao:
Online Knowledge Acquisition with the Selective Inherited Model. IJCNN 2020: 1-7 - [c65]Deepak Kadetotad, Jian Meng, Visar Berisha, Chaitali Chakrabarti, Jae-sun Seo:
Compressing LSTM Networks with Hierarchical Coarse-Grain Sparsity. INTERSPEECH 2020: 21-25 - [c64]Wonbo Shim, Yandong Luo, Jae-sun Seo, Shimeng Yu:
Impact of Read Disturb on Multilevel RRAM based Inference Engine: Experiments and Model Prediction. IRPS 2020: 1-5 - [c63]Yandong Luo, Xiaochen Peng, Ryan Hatcher, Titash Rakshit, Jorge Kittl, Mark S. Rodder, Jae-Sun Seo, Shimeng Yu:
A Variation Robust Inference Engine Based on STT-MRAM with Parallel Read-Out. ISCAS 2020: 1-5 - [c62]Shreyas K. Venkataramanaiah, Shihui Yin, Yu Cao, Jae-Sun Seo:
Deep Neural Network Training Accelerator Designs in ASIC and FPGA. ISOCC 2020: 21-22 - [c61]Usama Awais, Jae-sun Seo:
Regulation Control Design Techniques for Integrated Switched Capacitor Voltage Regulators. MWSCAS 2020: 186-189 - [i9]Colby R. Banbury, Vijay Janapa Reddi, Max Lam, William Fu, Amin Fazel, Jeremy Holleman, Xinyuan Huang, Robert Hurtado, David Kanter, Anton Lokhmotov, David A. Patterson, Danilo Pau, Jae-sun Seo, Jeff Sieracki, Urmish Thakker, Marian Verhelst, Poonam Yadav:
Benchmarking TinyML Systems: Challenges and Direction. CoRR abs/2003.04821 (2020)
2010 – 2019
- 2019
- [j23]Chia-Yu Chen, Boris Murmann, Jae-sun Seo, Hoi-Jun Yoo:
Custom Sub-Systems and Circuits for Deep Learning: Guest Editorial Overview. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(2): 247-252 (2019) - [j22]Jae-sun Seo, Yu Cao, Xin Li, Paul N. Whatmough:
Guest Editors' Introduction to the Special Section on Hardware and Algorithms for Energy-Constrained On-chip Machine Learning. ACM J. Emerg. Technol. Comput. Syst. 15(2): 14:1-14:2 (2019) - [j21]Jae-Sun Seo, Yu Cao, Xin Li, Paul N. Whatmough:
Guest Editors' Introduction: Hardware and Algorithms for Energy-Constrained On-Chip Machine Learning (Part 2). ACM J. Emerg. Technol. Comput. Syst. 15(4): 31:1-31:2 (2019) - [j20]Shihui Yin, Minkyu Kim, Deepak Kadetotad, Yang Liu, Chisung Bae, Sang Joon Kim, Yu Cao, Jae-sun Seo:
A 1.06- $\mu$ W Smart ECG Processor in 65-nm CMOS for Real-Time Biometric Authentication and Personal Cardiac Monitoring. IEEE J. Solid State Circuits 54(8): 2316-2326 (2019) - [j19]Shihui Yin, Jae-sun Seo, Yulhwa Kim, Xu Han, Hugh J. Barnaby, Shimeng Yu, Yandong Luo, Wangxin He, Xiaoyu Sun, Jae-Joon Kim:
Monolithically Integrated RRAM- and CMOS-Based In-Memory Computing Optimizations for Efficient Deep Learning. IEEE Micro 39(6): 54-63 (2019) - [j18]Minkyu Kim, Abinash Mohanty, Deepak Kadetotad, Luning Wei, Xiaofei He, Yu Cao, Jae-sun Seo:
A Real-Time 17-Scale Object Detection Accelerator With Adaptive 2000-Stage Classification in 65 nm CMOS. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(10): 3843-3853 (2019) - [c60]Zhewei Jiang, Shihui Yin, Minkyu Kim, Tushar Gupta, Mingoo Seok, Jae-sun Seo:
Vesti: An In-Memory Computing Processor for Deep Neural Networks Acceleration. ACSSC 2019: 1516-1521 - [c59]Sai Kiran Cherupally, Shihui Yin, Deepak Kadetotad, Chisung Bae, Sang Joon Kim, Jae-Sun Seo:
A Smart Hardware Security Engine Combining Entropy Sources of ECG, HRV and SRAM PUF for Authentication and Secret Key Generation. A-SSCC 2019: 145-148 - [c58]Deepak Kadetotad, Visar Berisha, Chaitali Chakrabarti, Jae-Sun Seo:
A 8.93-TOPS/W LSTM Recurrent Neural Network Accelerator Featuring Hierarchical Coarse-Grain Sparsity With All Parameters Stored On-Chip. ESSCIRC 2019: 119-122 - [c57]Zhewei Jiang, Shihui Yin, Jae-Sun Seo, Mingoo Seok:
C3SRAM: In-Memory-Computing SRAM Macro Based on Capacitive-Coupling Computing. ESSCIRC 2019: 131-134 - [c56]Shreyas Kolala Venkataramanaiah, Yufei Ma, Shihui Yin, Eriko Nurvitadhi, Aravind Dasu, Yu Cao, Jae-sun Seo:
Automatic Compiler Based FPGA Accelerator for CNN Training. FPL 2019: 166-172 - [c55]Zhewei Jiang, Shihui Yin, Jae-sun Seo, Mingoo Seok:
XNOR-SRAM: In-Bitcell Computing SRAM Macro based on Resistive Computing Mechanism. ACM Great Lakes Symposium on VLSI 2019: 417-422 - [c54]Gaurav Srivastava, Deepak Kadetotad, Shihui Yin, Visar Berisha, Chaitali Chakrabarti, Jae-sun Seo:
Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks. ICASSP 2019: 1393-1397 - [c53]Shruti R. Kulkarni, Deepak Vinayak Kadetotad, Shihui Yin, Jae-Sun Seo, Bipin Rajendran:
Neuromorphic Hardware Accelerator for SNN Inference based on STT-RAM Crossbar Arrays. ICECS 2019: 438-441 - [c52]Sai Kiran Cherupally, Gaurav Srivastava, Shihui Yin, Deepak Kadetotad, Chisung Bae, Sang Joon Kim, Jae-sun Seo:
ECG Authentication Neural Network Hardware Design with Collective Optimization of Low Precision and Structured Compression. ISCAS 2019: 1-5 - [c51]Jyotishman Saikia, Shihui Yin, Zhewei Jiang, Mingoo Seok, Jae-sun Seo:
K-Nearest Neighbor Hardware Accelerator Using In-Memory Computing SRAM. ISLPED 2019: 1-6 - [c50]Xiaochen Peng, Minkyu Kim, Xiaoyu Sun, Shihui Yin, Titash Rakshit, Ryan M. Hatcher, Jorge A. Kittl, Jae-sun Seo, Shimeng Yu:
Inference engine benchmarking across technological platforms from CMOS to RRAM. MEMSYS 2019: 471-479 - [c49]Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina:
FixyNN: Energy-Efficient Real-Time Mobile Computer Vision Hardware Acceleration via Transfer Learning. MLSys 2019 - [c48]Mingoo Seok, Minhao Yang, Zhewei Jiang, Aurel A. Lazar, Jae-sun Seo:
Cases for Analog Mixed Signal Computing Integrated Circuits for Deep Neural Networks. VLSI-DAT 2019: 1-2 - [i8]Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina:
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning. CoRR abs/1902.11128 (2019) - [i7]Shreyas Kolala Venkataramanaiah, Yufei Ma, Shihui Yin, Eriko Nurvitadhi, Aravind Dasu, Yu Cao, Jae-sun Seo:
Automatic Compiler Based FPGA Accelerator for CNN Training. CoRR abs/1908.06724 (2019) - [i6]Shihui Yin, Xiaoyu Sun, Shimeng Yu, Jae-sun Seo:
High-Throughput In-Memory Computing for Binary Deep Neural Networks with Monolithically Integrated RRAM and 90nm CMOS. CoRR abs/1909.07514 (2019) - 2018
- [j17]Arindam Basu, Meng-Fan Chang, Elisabetta Chicca, Tanay Karnik, Hai Helen Li, Jae-sun Seo:
Guest Editorial Low-Power, Adaptive Neuromorphic Systems: Devices, Circuit, Architectures and Algorithms. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(1): 1-5 (2018) - [j16]Arindam Basu, Jyotibdha Acharya, Tanay Karnik, Huichu Liu, Hai Helen Li, Jae-sun Seo, Chang Song:
Low-Power, Adaptive Neuromorphic Systems: Recent Progress and Future Directions. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(1): 6-27 (2018) - [j15]Yufei Ma, Naveen Suda, Yu Cao, Sarma B. K. Vrudhula, Jae-sun Seo:
ALAMO: FPGA acceleration of deep learning algorithms with a modularized RTL compiler. Integr. 62: 14-23 (2018) - [j14]Yu Cao, Xin Li, Jae-sun Seo, Ganesh Dasika:
Guest Editors' Introduction: Frontiers of Hardware and Algorithms for On-chip Learning. ACM J. Emerg. Technol. Comput. Syst. 14(2): 14:1-14:2 (2018) - [j13]Kyungwook Chang, Deepak Kadetotad, Yu Cao, Jae-sun Seo, Sung Kyu Lim:
Power, Performance, and Area Benefit of Monolithic 3D ICs for On-Chip Deep Neural Networks Targeting Speech Recognition. ACM J. Emerg. Technol. Comput. Syst. 14(4): 42:1-42:19 (2018) - [j12]Robert D'Angelo, Xiaocong Du, Christopher D. Salthouse, Brent Hollosi, Geremy Freifeld, Wes Uy, Haiyao Huang, Nhut Tran, Armand Chery, Jae-sun Seo, Yu Cao, Dorothy C. Poppe, Sameer R. Sonkusale:
Process Scalability of Pulse-Based Circuits for Analog Image Convolution. IEEE Trans. Circuits Syst. I Regul. Pap. 65-I(9): 2929-2938 (2018) - [j11]Yufei Ma, Yu Cao, Sarma B. K. Vrudhula, Jae-sun Seo:
Optimizing the Convolution Operation to Accelerate Deep Neural Networks on FPGA. IEEE Trans. Very Large Scale Integr. Syst. 26(7): 1354-1367 (2018) - [j10]Mohit Shah, Sairam Arunachalam, Jingcheng Wang, David T. Blaauw, Dennis Sylvester, Hun-Seok Kim, Jae-sun Seo, Chaitali Chakrabarti:
A Fixed-Point Neural Network Architecture for Speech Applications on Resource Constrained Hardware. J. Signal Process. Syst. 90(5): 727-741 (2018) - [c47]Xiaoyu Sun, Xiaochen Peng, Pai-Yu Chen, Rui Liu, Jae-sun Seo, Shimeng Yu:
Fully parallel RRAM synaptic array for implementing binary neural network with (+1, -1) weights and (+1, 0) neurons. ASP-DAC 2018: 574-579 - [c46]Xiaoyu Sun, Shihui Yin, Xiaochen Peng, Rui Liu, Jae-sun Seo, Shimeng Yu:
XNOR-RRAM: A scalable and parallel resistive synaptic architecture for binary neural networks. DATE 2018: 1423-1428 - [c45]Avesta Sasan, Qi Zhu, Yanzhi Wang, Jae-sun Seo, Tinoosh Mohsenin:
Low Power and Trusted Machine Learning. ACM Great Lakes Symposium on VLSI 2018: 515 - [c44]Prad Kadambi, Abinash Mohanty, Hao Ren, Jaclyn Smith, Kevin McGuinnes, Kimberly Holt, Armin Furtwaengler, Roberto Slepetys, Zheng Yang, Jae-sun Seo, Junseok Chae, Yu Cao, Visar Berisha:
Towards a Wearable Cough Detector Based on Neural Networks. ICASSP 2018: 2161-2165 - [c43]Yufei Ma, Tu Zheng, Yu Cao, Sarma B. K. Vrudhula, Jae-sun Seo:
Algorithm-hardware co-design of single shot detector for fast object detection on FPGAs. ICCAD 2018: 57 - [c42]Shihui Yin, Xiaoyu Sun, Shimeng Yu, Jae-sun Seo, Chaitali Chakrabarti:
A Parallel RRAM Synaptic Array Architecture for Energy-Efficient Recurrent Neural Networks. SiPS 2018: 13-18 - [i5]Shihui Yin, Gaurav Srivastava, Shreyas K. Venkataramanaiah, Chaitali Chakrabarti, Visar Berisha, Jae-sun Seo:
Minimizing Area and Energy of Deep Learning Hardware Design Using Collective Low Precision and Structured Compression. CoRR abs/1804.07370 (2018) - [i4]Chetan Singh Thakur, Jamal Molin, Gert Cauwenberghs, Giacomo Indiveri, Kundan Kumar, Ning Qiao, Johannes Schemmel, Runchun Wang, Elisabetta Chicca, Jennifer Olson Hasler, Jae-sun Seo, Shimeng Yu, Yu Cao, André van Schaik, Ralph Etienne-Cummings:
Large-Scale Neuromorphic Spiking Array Processors: A quest to mimic the brain. CoRR abs/1805.08932 (2018) - 2017
- [j9]Zihan Xu, Steven Skorheim, Ming Tu, Visar Berisha, Shimeng Yu, Jae-sun Seo, Maxim Bazhenov, Yu Cao:
Improving efficiency in sparse learning with the feedforward inhibitory motif. Neurocomputing 267: 141-151 (2017) - [j8]Jiangyi Li, Jae-sun Seo, Ioannis Kymissis, Mingoo Seok:
Triple-Mode, Hybrid-Storage, Energy Harvesting Power Management Unit: Achieving High Efficiency Against Harvesting and Load Power Variabilities. IEEE J. Solid State Circuits 52(10): 2550-2562 (2017) - [c41]Shihui Yin, Gaurav Srivastava, Shreyas K. Venkataramanaiah, Chaitali Chakrabarti, Visar Berisha, Jae-sun Seo:
Minimizing area and energy of deep learning hardware design using collective low precision and structured compression. ACSSC 2017: 1907-1911 - [c40]Minkyu Kim, Abinash Mohanty, Deepak Kadetotad, Naveen Suda, Luning Wei, Pooja Saseendran, Xiaofei He, Yu Cao, Jae-sun Seo:
A real-time 17-scale object detection accelerator with adaptive 2000-stage classification in 65nm CMOS. ASP-DAC 2017: 21-22 - [c39]Shunti Yin, Deepak Kadetotad, Bonan Yan, Chang Song, Yiran Chen, Chaitali Chakrabarti, Jae-sun Seo:
Low-power neuromorphic speech recognition engine with coarse-grain sparsity. ASP-DAC 2017: 111-114 - [c38]