| Optimization principles and application performance evaluation of a multithreaded GPU using CUDA S Ryoo, CI Rodrigues, SS Baghsorkhi, SS Stone, DB Kirk, WW Hwu Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of …, 2008 | 1330 | 2008 |
| An adaptive performance modeling tool for GPU architectures SS Baghsorkhi, M Delahaye, SJ Patel, WD Gropp, WW Hwu Proceedings of the 15th ACM SIGPLAN symposium on Principles and practice of …, 2010 | 437 | 2010 |
| Program optimization space pruning for a multithreaded GPU S Ryoo, CI Rodrigues, SS Stone, SS Baghsorkhi, SZ Ueng, JA Stratton, ... Proceedings of the 6th annual IEEE/ACM international symposium on Code …, 2008 | 393 | 2008 |
| CUDA-lite: Reducing GPU programming complexity SZ Ueng, M Lathara, SS Baghsorkhi, WMW Hwu Languages and Compilers for Parallel Computing: 21th International Workshop …, 2008 | 336 | 2008 |
| Program optimization carving for GPU computing S Ryoo, CI Rodrigues, SS Stone, JA Stratton, SZ Ueng, SS Baghsorkhi, ... Journal of Parallel and Distributed Computing 68 (10), 1389-1401, 2008 | 171 | 2008 |
| Function as a service (FaaS) system enhancements MR Haghighat, K Doshi, AJ Herdrich, A Mohan, RR Iyer, M Sun, K Bhuyan, ... US Patent 11,922,220, 2024 | 148 | 2024 |
| Programmable coarse grained and sparse matrix compute hardware with advanced scheduling E Nurvitadhi, B Vembu, NCG Von Borries, R Barik, TH Lin, K Sinha, ... US Patent 10,186,011, 2019 | 138 | 2019 |
| Compute optimizations for neural networks K Nealis, A Yao, X Chen, E Ould-Ahmed-Vall, SS Baghsorkhi, ... US Patent 10,410,098, 2019 | 109 | 2019 |
| Auto-tuning of fast fourier transform on graphics processors Y Dotsenko, SS Baghsorkhi, B Lloyd, NK Govindaraju ACM SIGPLAN Notices 46 (8), 257-266, 2011 | 99 | 2011 |
| Implicitly parallel programming models for thousand-core microprocessors W Hwu, S Ryoo, SZ Ueng, JH Kelm, I Gelado, SS Stone, RE Kidd, ... Proceedings of the 44th annual Design Automation Conference, 754-759, 2007 | 98 | 2007 |
| Specialized fixed function hardware for efficient convolution R Barik, E Ould-Ahmed-Vall, X Chen, D Srivastava, A Yao, K Nealis, ... US Patent 10,824,938, 2020 | 84 | 2020 |
| Coordination and increased utilization of graphics processors during inference AR Appu, A Koker, JC Weast, MB MacPherson, LL Hurd, SS Baghsorkhi, ... US Patent 10,304,154, 2019 | 77 | 2019 |
| Performance analysis and tuning for general purpose graphics processing units (GPGPU) H Kim, R Vuduc, S Baghsorkhi Morgan & Claypool Publishers, 2012 | 76 | 2012 |
| Efficient performance evaluation of memory hierarchy for highly multithreaded graphics processors SS Baghsorkhi, I Gelado, M Delahaye, WW Hwu ACM SIGPLAN Notices 47 (8), 23-34, 2012 | 69 | 2012 |
| Methods and apparatus to detect anomalies of a monitored system M Agerstam, B Sadeghi, J Martin, J Ota, J Gottschlich, M Carranza, ... US Patent 10,802,942, 2020 | 61 | 2020 |
| Compute optimizations for low precision machine learning operations E Ould-Ahmed-Vall, SS Baghsorkhi, A Yao, K Nealis, X Chen, A Koker, ... US Patent 10,242,423, 2019 | 59 | 2019 |
| Program optimization study on a 128-core GPU S Ryoo, C Rodrigues, S Stone, S Baghsorkhi, SZ Ueng, WW Hwu The First Workshop on General Purpose Processing on Graphics Processing …, 2007 | 48 | 2007 |
| Save: Sparsity-aware vector engine for accelerating dnn training and inference on cpus Z Gong, H Ji, CW Fletcher, CJ Hughes, S Baghsorkhi, J Torrellas 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture …, 2020 | 46 | 2020 |
| Compute optimizations for low precision machine learning operations E Ould-Ahmed-Vall, SS Baghsorkhi, A Yao, K Nealis, X Chen, A Koker, ... US Patent 10,726,514, 2020 | 46 | 2020 |
| FlexVec: Auto-vectorization for irregular loops SS Baghsorkhi, N Vasudevan, Y Wu Proceedings of the 37th ACM SIGPLAN Conference on Programming Language …, 2016 | 38 | 2016 |
Wen-mei W. HwuSenior Distinguished Research Scientist, NVIDIA; Professor and Sanders-AMD Chair of Electrical and在 illinois.edu 的电子邮件经过验证
