| {TensorFlow}: a system for {Large-Scale} machine learning M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... 12th USENIX symposium on operating systems design and implementation (OSDI …, 2016 | 47081 | 2016 |
| Revisiting distributed synchronous SGD J Chen, X Pan, R Monga, S Bengio, R Jozefowicz arXiv preprint arXiv:1604.00981, 2016 | 963 | 2016 |
| Tensorflow: A system for large-scale machine learning A Martín, B Paul, C Jianmin, C Zhifeng, D Andy, D Jeffrey, D Matthieu, ... 12th USENIX symposium on operating systems design and implementation (OSDI …, 2016 | 517 | 2016 |
| 12th USENIX symposium on operating systems design and implementation (OSDI 16) M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... Savannah, GA, 265-283, 2016 | 306* | 2016 |
| Statistical GPU power analysis using tree-based methods J Chen, B Li, Y Zhang, L Peng, J Peir 2011 International Green Computing Conference and Workshops, 1-6, 2011 | 68 | 2011 |
| & Kudlur, M.(2016, November). Tensorflow: a system for large-scale machine learning M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean Proceedings of the 12th USENIX Symposium on Operating Systems Design and …, 0 | 51 | |
| Architecture comparisons between Nvidia and ATI GPUs: Computation parallelism and data communications Y Zhang, L Peng, B Li, JK Peir, J Chen 2011 IEEE international symposium on workload characterization (IISWC), 205-215, 2011 | 50 | 2011 |
| TensorFlow: A system for large-scale machine learning. arXiv 2016 M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... arXiv preprint arXiv:1605.08695, 0 | 46 | |
| Tree structured analysis on GPU power study J Chen, B Li, Y Zhang, L Peng, J Peir 2011 IEEE 29th International Conference on Computer Design (ICCD), 57-64, 2011 | 43 | 2011 |
| Guided region-based GPU scheduling: utilizing multi-thread parallelism to hide memory latency J Chen, X Tao, Z Yang, JK Peir, X Li, SL Lu 2013 IEEE 27th International Symposium on Parallel and Distributed …, 2013 | 39 | 2013 |
| TensorFlow: A System for Large-Scale Machine Learning TensorFlow: A system for large-scale machine learning M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... Proceedings of the 12th USENIX Symposium on Operating Systems Design and …, 2009 | 22 | 2009 |
| Revisiting distributed synchronous SGD. arXiv 2016 J Chen, X Pan, R Monga, S Bengio, R Jozefowicz arXiv preprint arXiv:1604.00981, 0 | 18 | |
| Revisiting distributed synchronous SGD. CoRR abs/1604.00981 (2016) J Chen, R Monga, S Bengio, R Józefowicz arXiv preprint arXiv:1604.00981, 2016 | 11 | 2016 |
| Revisiting distributed synchronous sgd.(2016) J Chen, X Pan, R Monga, S Bengio, R Jozefowicz arXiv preprint arXiv:1604.00981, 2016 | 9 | 2016 |
| Weak execution ordering-exploiting iterative methods on many-core gpus J Chen, Z Huang, F Su, JK Peir, J Ho, L Peng 2010 IEEE International Symposium on Performance Analysis of Systems …, 2010 | 7 | 2010 |
| TensorFlow: a system for large-scale machine learning this paper is included in the proceedings of the TensorFlow: a system for large-scale machine learning M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... Proceedings of the 12th USENIX conference on Operating Systems Design and …, 0 | 5 | |
| Proceedings of the 12th USENIX conference on Operating Systems Design and Implementation (OSDI’16) A Martín, B Paul, C Jianmin, C Zhifeng, D Andy, D Jeffrey, D Matthieu, ... USENIX Association, 2016 | 2 | 2016 |
| Performance and power comparisons between Nvidia and ATI GPUs Y Zhang, L Peng, B Li, JK Peir, J Chen International Journal of Computer Science & Information Technology 6 (6), 1, 2014 | 2 | 2014 |
| Adaptive Dropout: A Novel Regularization Technique for Deep Neural Networks M Abadi, P Barham, J Chen, Z Chen | 1 | |
| PERFORMANCE AND POWE R COMPARISONS BE-TWEEN NVIDIAAND ATI GPUS Y Zhang, L Peng, B Li, JK Peir, J Chen | | |
