Learning both weights and connections for efficient neural network S Han, J Pool, J Tran, W Dally Advances in neural information processing systems 28, 2015 | 7684 | 2015 |
cudnn: Efficient primitives for deep learning S Chetlur, C Woolley, P Vandermersch, J Cohen, J Tran, B Catanzaro, ... arXiv preprint arXiv:1410.0759, 2014 | 2285 | 2014 |
Dsd: Dense-sparse-dense training for deep neural networks S Han, J Pool, S Narang, H Mao, E Gong, S Tang, E Elsen, P Vajda, ... arXiv preprint arXiv:1607.04381, 2016 | 237 | 2016 |
All-frequency interactive relighting of translucent objects with single and multiple scattering R Wang, J Tran, D Luebke ACM Transactions on Graphics (TOG) 24 (3), 1202-1207, 2005 | 122 | 2005 |
All-Frequency Relighting of Non-Diffuse Objects using Separable BRDF Approximation. R Wang, J Tran, DP Luebke Rendering Techniques, 345-354, 2004 | 117 | 2004 |
DSD: regularizing deep neural networks with dense-sparse-dense training flow S Han, J Pool, S Narang, H Mao, S Tang, E Elsen, B Catanzaro, J Tran, ... arXiv preprint arXiv:1607.04381 3 (6), 2016 | 94 | 2016 |
cuDNN: Efficient primitives for deep learning. CoRR abs/1410.0759 (2014) S Chetlur, C Woolley, P Vandermersch, J Cohen, J Tran, B Catanzaro, ... arXiv preprint arXiv:1410.0759, 2014 | 57 | 2014 |
Rhythm: Harnessing data parallel hardware for server workloads SR Agrawal, V Pistol, J Pang, J Tran, D Tarjan, AR Lebeck ACM SIGPLAN Notices 49 (4), 19-34, 2014 | 53 | 2014 |
All-frequency relighting of glossy objects R Wang, J Tran, D Luebke ACM Transactions on Graphics (TOG) 25 (2), 293-318, 2006 | 53 | 2006 |
Indirectly accessing sample data to perform multi-convolution operations in a parallel processing system JC WOOLLEY, J Tran US Patent 10,255,547, 2019 | 31 | 2019 |
Parallel support vector machines in practice S Tyree, JR Gardner, KQ Weinberger, K Agrawal, J Tran arXiv preprint arXiv:1404.1066, 2014 | 31 | 2014 |
New challenges for cellular automata simulation on the GPU J Tran, D Jordan, D Luebke SIGGRAPH, Los Angeles. ACM. Poster, 2004 | 29 | 2004 |
Inline data inspection for workload simplification JM Pool, A Kerr, J Tran, MY Siu, S Oberman US Patent 10,503,507, 2019 | 18 | 2019 |
Managing data sparsity for neural networks J Pool, G Venkatesh, JA Latorre, J Choquette, R Krashinsky, J Tran, F Xie, ... US Patent 11,392,829, 2022 | 13 | 2022 |
Sense amp design in SOI M Golden, J Tran, B McGee, B Kuo 2005 IEEE International SOI Conference Proceedings, 118-120, 2005 | 9 | 2005 |
CUTLASS: CUDA Template Library for Dense Linear Algebra at all levels and scales A Kerr, D Merrill, J Demouth, J Tran, N Farooqui, M Tavenrath, V Schuster, ... NVIDIA GPU Technology Conference (GTC) s8854 (Mar 2018), 2018 | 5 | 2018 |
Proceedings of Eurographics Symposium on Rendering L Wang, J Tran, D Luebke | 3 | 2004 |
Kernel fusion for machine learning A Kerr, M Murphy, M Hagog, J Demouth, J Tran US Patent App. 16/591,306, 2021 | 2 | 2021 |
IOAgent: Leveraging the Application Analysis of Workload Effects S Gómez-Villamor, J Tran, S Rees, V Muntés-Mulero, JL Larriba-Pey Technical Report UPC-DAC-RR-2005-49, Department of Computer Architecture …, 2005 | 2 | 2005 |
Method and apparatus for efficient access to multidimensional data structures and/or other large data blocks AL Minkin, A Kaatz, O Giroux, J Choquette, S Gadre, M Patel, J Tran, ... US Patent App. 17/691,276, 2023 | 1 | 2023 |