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ORCIDCODES+ISSS 2022: Shanghai, China
- International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS 2022, Shanghai, China, October 7-14, 2022. IEEE 2022, ISBN 978-1-6654-7294-4
- Xiangzhong Luo, Di Liu, Hao Kong, Shuo Huai, Hui Chen, Weichen Liu:
Work-in-Progress: What to Expect of Early Training Statistics? An Investigation on Hardware-Aware Neural Architecture Search. 1-2 - Nan Hu, Chao Wang, Xuehai Zhou, Xi Li:
Work-in-Progress: Scheduler for Collaborated FPGA-GPU-CPU Based on Intermediate Language. 3-4 - Tianyou Bao
, José Luis Imaña, Pengzhou He, Jiafeng Xie:
Work-in-Progress: High-Performance Systolic Hardware Accelerator for RBLWE-based Post-Quantum Cryptography. 5-6 - Yunji Qin, Lei Gong, Zhendong Zheng, Chao Wang:
Work-in-Progress: BloCirNN: An Efficient Software/hardware Codesign Approach for Neural Network Accelerators with Block-Circulant Matrix. 7-8 - Yingxue Gao, Lei Gong, Chao Wang, Xuehai Zhou:
Work-in-Progress: HeteroRW: A Generalized and Efficient Framework for Random Walks in Graph Analysis. 9-10 - Jianan Yuan, Huan Liu, Shangyu Wu, Yiquan Lin, Tiantian Wang, Chenlin Ma, Rui Mao, Yi Wang:
Work-in-Progress: Lark: A Learned Secondary Index Toward LSM-tree for Resource-Constrained Embedded Storage Systems. 11-12 - Yueting Li, Bingluo Zhao, Xinyi Xu, Yundong Zhang, Jun Wang, Weisheng Zhao:
Work-in-Progress: Toward Energy-efficient Near STT-MRAM Processing Architecture for Neural Networks. 13-14 - Negin Firouzian, Seyyed Hasan Mozafari, James J. Clark, Warren J. Gross, Brett H. Meyer:
Work-in-Progress: Utilizing latency and accuracy predictors for efficient hardware-aware NAS. 15-16 - Binyi Wu, Wolfgang Furtner, Bernd Waschneck, Christian Mayr:
Industry-track: Towards Agile Design of Neural Processing Unit. 17-20 - Roderick Bloem, Alberto Larrauri, Roland Lengfeldner, Cristinel Mateis, Dejan Nickovic, Björn Ziegler:
Industry Paper: Surrogate Models for Testing Analog Designs under Limited Budget - a Bandgap Case Study. 21-24 - Hussam Amrouch, Mohsen Imani, Xun Jiao, Yiannis Aloimonos, Cornelia Fermüller, Dehao Yuan, Dongning Ma, Hamza Errahmouni Barkam, Paul R. Genssler, Peter Sutor Jr.:
Brain-Inspired Hyperdimensional Computing for Ultra-Efficient Edge AI. 25-34
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