| Rtmobile: Beyond real-time mobile acceleration of rnns for speech recognition P Dong, S Wang, W Niu, C Zhang, S Lin, Z Li, Y Gong, B Ren, X Lin, ... 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 56 | 2020 |
| CurvaNet: Geometric deep learning based on directional curvature for 3D shape analysis W He, Z Jiang, C Zhang, AM Sainju Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 37 | 2020 |
| Improving dnn fault tolerance using weight pruning and differential crossbar mapping for reram-based edge ai G Yuan, Z Liao, X Ma, Y Cai, Z Kong, X Shen, J Fu, Z Li, C Zhang, H Peng, ... 2021 22nd International Symposium on Quality Electronic Design (ISQED), 135-141, 2021 | 32 | 2021 |
| Wavesz: A hardware-algorithm co-design of efficient lossy compression for scientific data J Tian, S Di, C Zhang, X Liang, S Jin, D Cheng, D Tao, F Cappello Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of …, 2020 | 26 | 2020 |
| H-gcn: A graph convolutional network accelerator on versal acap architecture C Zhang, T Geng, A Guo, J Tian, M Herbordt, A Li, D Tao 2022 32nd International Conference on Field-Programmable Logic and …, 2022 | 21 | 2022 |
| A neuromorphic-hardware oriented bio-plausible online-learning spiking neural network model GC Qiao, SG Hu, JJ Wang, CM Zhang, TP Chen, N Ning, Q Yu, Y Liu IEEE Access 7, 71730-71740, 2019 | 20 | 2019 |
| Comet: a novel memory-efficient deep learning training framework by using error-bounded lossy compression S Jin, C Zhang, X Jiang, Y Feng, H Guan, G Li, SL Song, D Tao arXiv preprint arXiv:2111.09562, 2021 | 18 | 2021 |
| ClickTrain: efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning C Zhang, G Yuan, W Niu, J Tian, S Jin, D Zhuang, Z Jiang, Y Wang, B Ren, ... Proceedings of the ACM International Conference on Supercomputing, 266–278, 2021 | 17 | 2021 |
| Deepspeed ulysses: System optimizations for enabling training of extreme long sequence transformer models SA Jacobs, M Tanaka, C Zhang, M Zhang, L Song, S Rajbhandari, Y He arXiv preprint arXiv:2309.14509, 2023 | 15 | 2023 |
| A versatile neuromorphic system based on simple neuron model CM Zhang, GC Qiao, SG Hu, JJ Wang, ZW Liu, YA Liu, Q Yu, Y Liu AIP Advances 9 (1), 2019 | 8 | 2019 |
| Tdc: Towards extremely efficient cnns on gpus via hardware-aware tucker decomposition L Xiang, M Yin, C Zhang, A Sukumaran-Rajam, P Sadayappan, B Yuan, ... Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and …, 2023 | 6 | 2023 |
| CEAZ: accelerating parallel I/O via hardware-algorithm co-designed adaptive lossy compression C Zhang, S Jin, T Geng, J Tian, A Li, D Tao Proceedings of the 36th ACM International Conference on Supercomputing, 1-13, 2022 | 6 | 2022 |
| HALOC: hardware-aware automatic low-rank compression for compact neural networks J Xiao, C Zhang, Y Gong, M Yin, Y Sui, L Xiang, D Tao, B Yuan Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10464 …, 2023 | 4 | 2023 |
| DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies SL Song, B Kruft, M Zhang, C Li, S Chen, C Zhang, M Tanaka, X Wu, ... arXiv preprint arXiv:2310.04610, 2023 | 2 | 2023 |
| HRBP: Hardware-friendly Regrouping towards Block-based Pruning for Sparse CNN Training H Ma, C Zhang, X Ma, G Yuan, W Zhang, S Liu, T Chen, D Tao, Y Wang, ... Conference on Parsimony and Learning, 282-301, 2024 | 1 | 2024 |
| SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates B Sun, X Yu, C Zhang, J Tian, S Jin, K Iskra, T Zhou, T Bicer, P Beckman, ... arXiv preprint arXiv:2211.00224, 2022 | 1 | 2022 |
| Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors C Zhang, B Sun, X Yu, Z Xie, W Zheng, KA Iskra, P Beckman, D Tao Proceedings of the SC'23 Workshops of The International Conference on High …, 2023 | | 2023 |
| HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs C Zhang, S Smith, B Sun, J Tian, J Soifer, X Yu, SL Song, Y He, D Tao Proceedings of the 37th International Conference on Supercomputing, 324-335, 2023 | | 2023 |
Dingwen TaoIndiana University Bloomington, IEEE/ACM Senior Member在 iu.edu 的电子邮件经过验证
