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Jae-sun Seo
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Publications
- 2023
- [c105]Zhenyu Wang, Jingbo Sun, A. Alper Goksoy, Sumit K. Mandal, Jae-Sun Seo, Chaitali Chakrabarti, Ümit Y. Ogras, Vidya A. Chhabria, Yu Cao:
Benchmarking Heterogeneous Integration with 2.5D/3D Interconnect Modeling. ASICON 2023: 1-4 - 2022
- [j42]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) - [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 - 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 - [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) - [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) - [c65]Deepak Kadetotad, Jian Meng, Visar Berisha, Chaitali Chakrabarti, Jae-sun Seo:
Compressing LSTM Networks with Hierarchical Coarse-Grain Sparsity. INTERSPEECH 2020: 21-25 - 2019
- [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 - [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 - 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) - [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) - 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 - [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]Shihui Yin, Shreyas K. Venkataramanaiah, Gregory K. Chen, Ram Krishnamurthy, Yu Cao, Chaitali Chakrabarti, Jae-sun Seo:
Algorithm and hardware design of discrete-time spiking neural networks based on back propagation with binary activations. BioCAS 2017: 1-5 - [i3]Shihui Yin, Shreyas K. Venkataramanaiah, Gregory K. Chen, Ram Krishnamurthy, Yu Cao, Chaitali Chakrabarti, Jae-sun Seo:
Algorithm and Hardware Design of Discrete-Time Spiking Neural Networks Based on Back Propagation with Binary Activations. CoRR abs/1709.06206 (2017) - 2016
- [c24]Deepak Kadetotad, Sairam Arunachalam, Chaitali Chakrabarti, Jae-sun Seo:
Efficient memory compression in deep neural networks using coarse-grain sparsification for speech applications. ICCAD 2016: 78
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