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Bojian Zheng
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Benchmarking and analyzing deep neural network training
H Zhu, M Akrout, B Zheng, A Pelegris, A Jayarajan, A Phanishayee, ...
2018 IEEE International Symposium on Workload Characterization (IISWC), 88-100, 2018
1362018
Tbd: Benchmarking and analyzing deep neural network training
H Zhu, M Akrout, B Zheng, A Pelegris, A Phanishayee, B Schroeder, ...
arXiv preprint arXiv:1803.06905, 2018
812018
Echo: Compiler-based GPU memory footprint reduction for LSTM RNN training
B Zheng, N Vijaykumar, G Pekhimenko
2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture …, 2020
352020
Automatic horizontal fusion for GPU kernels
A Li, B Zheng, G Pekhimenko, F Long
2022 IEEE/ACM International Symposium on Code Generation and Optimization …, 2022
252022
DietCode: Automatic optimization for dynamic tensor programs
B Zheng, Z Jiang, CH Yu, H Shen, J Fromm, Y Liu, Y Wang, L Ceze, ...
Proceedings of Machine Learning and Systems 4, 848-863, 2022
232022
IDEAL: Image denoising accelerator
M Mahmoud, B Zheng, AD Lascorz, F Heide, J Assouline, P Boucher, ...
Proceedings of the 50th Annual IEEE/ACM International Symposium on …, 2017
192017
EcoRNN: Efficient computing of LSTM RNN training on gpus
B Zheng, A Tiwari, N Vijaykumar, G Pekhimenko
arXiv preprint arXiv:1805.08899, 2018
82018
Hidet: Task-mapping programming paradigm for deep learning tensor programs
Y Ding, CH Yu, B Zheng, Y Liu, Y Wang, G Pekhimenko
Proceedings of the 28th ACM International Conference on Architectural …, 2023
72023
DNN-Train: benchmarking and analyzing DNN training
H Zhu, B Zheng, B Schroeder, G Pekhimenko, A Phanishayee
Training 8, 16GBs, 2018
62018
Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction
M Andoorveedu, Z Zhu, B Zheng, G Pekhimenko
Advances in Neural Information Processing Systems 35, 12267-12282, 2022
22022
EcoRNN: Fused LSTM RNN Implementation with Data Layout Optimization
B Zheng, A Nair, Q Wu, N Vijaykumar, G Pekhimenko
arXiv preprint arXiv:1805.08899, 2018
22018
EcoRNN: Efficient Computing of LSTM RNN on GPUs
B Zheng, G Pekhimenko
Memory 9, 1735-1780, 1997
11997
Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUs
B Zheng, CH Yu, J Wang, Y Ding, Y Liu, Y Wang, G Pekhimenko
Proceedings of the 56th Annual IEEE/ACM International Symposium on …, 2023
2023
Domain-Specific Compilation
MG Olabi, JG Luna, O Mutlu, W Hwu, I El Hajj, A Li, B Zheng, ...
MiCRo 50 Author index
A Jaleel, AJ Elmore, A Bhattacharjee, A Holmes, AJ McPadden, ...
TBD SUITE: BENCHMARKING AND PROFILING TOOLS FOR DNNS
XY Geoffrey, H Zhu, A Jayarajan, B Zheng, A Tiwari, G Pekhimenko
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