| Halide: a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines J Ragan-Kelley, C Barnes, A Adams, S Paris, F Durand, S Amarasinghe Acm Sigplan Notices 48 (6), 519-530, 2013 | 1275 | 2013 |
| Opentuner: An extensible framework for program autotuning J Ansel, S Kamil, K Veeramachaneni, J Ragan-Kelley, J Bosboom, ... Proceedings of the 23rd international conference on Parallel architectures …, 2014 | 595 | 2014 |
| Decoupling algorithms from schedules for easy optimization of image processing pipelines J Ragan-Kelley, A Adams, S Paris, M Levoy, S Amarasinghe, F Durand ACM Transactions on Graphics (TOG) 31 (4), 1-12, 2012 | 304 | 2012 |
| DiffTaichi: Differentiable programming for physical simulation Y Hu, L Anderson, TM Li, Q Sun, N Carr, J Ragan-Kelley, F Durand International Conference on Learning Representations, 2020 | 244 | 2020 |
| Darkroom: compiling high-level image processing code into hardware pipelines. J Hegarty, J Brunhaver, Z DeVito, J Ragan-Kelley, N Cohen, S Bell, ... ACM Trans. Graph. 33 (4), 144:1-144:11, 2014 | 218 | 2014 |
| Automatically Scheduling Halide Image Processing Pipelines RT Mullapudi, A Adams, D Sharlet, J Ragan-Kelley, K Fatahalian ACM Transactions on Graphics (TOG) 35 (4), 2016 | 203 | 2016 |
| OpenFab: A programmable pipeline for multi-material fabrication K Vidimče, SP Wang, J Ragan-Kelley, W Matusik ACM Transactions on Graphics (TOG) 32 (4), 1-12, 2013 | 196 | 2013 |
| Learning to optimize halide with tree search and random programs A Adams, K Ma, L Anderson, R Baghdadi, TM Li, M Gharbi, B Steiner, ... ACM Transactions on Graphics (TOG) 38 (4), 1-12, 2019 | 186 | 2019 |
| Taichi: a language for high-performance computation on spatially sparse data structures Y Hu, TM Li, L Anderson, J Ragan-Kelley, F Durand ACM Transactions on Graphics (TOG) 38 (6), 1-16, 2019 | 129 | 2019 |
| Programming heterogeneous systems from an image processing DSL J Pu, S Bell, X Yang, J Setter, S Richardson, J Ragan-Kelley, M Horowitz ACM Transactions on Architecture and Code Optimization (TACO) 14 (3), 1-25, 2017 | 128 | 2017 |
| Portable performance on heterogeneous architectures PM Phothilimthana, J Ansel, J Ragan-Kelley, S Amarasinghe ACM SIGARCH Computer Architecture News 41 (1), 431-444, 2013 | 117 | 2013 |
| Decoupled sampling for graphics pipelines J Ragan-Kelley, J Lehtinen, J Chen, M Doggett, F Durand ACM Transactions on Graphics (TOG) 30 (3), 1-17, 2011 | 116 | 2011 |
| Differentiable programming for image processing and deep learning in Halide TM Li, M Gharbi, A Adams, F Durand, J Ragan-Kelley ACM Transactions on Graphics (ToG) 37 (4), 1-13, 2018 | 115 | 2018 |
| Serverless linear algebra V Shankar, K Krauth, K Vodrahalli, Q Pu, B Recht, I Stoica, ... Proceedings of the 11th ACM Symposium on Cloud Computing, 281-295, 2020 | 106* | 2020 |
| Halide: Decoupling algorithms from schedules for high-performance image processing J Ragan-Kelley, A Adams, D Sharlet, C Barnes, S Paris, M Levoy, ... Communications of the ACM 61 (1), 106-115, 2017 | 105 | 2017 |
| Rigel: Flexible multi-rate image processing hardware J Hegarty, R Daly, Z DeVito, J Ragan-Kelley, M Horowitz, P Hanrahan ACM Transactions on Graphics (TOG) 35 (4), 1-11, 2016 | 89 | 2016 |
| Proximal: Efficient image optimization using proximal algorithms F Heide, S Diamond, M Nießner, J Ragan-Kelley, W Heidrich, G Wetzstein ACM Transactions on Graphics (TOG) 35 (4), 1-15, 2016 | 82 | 2016 |
| Neural kernels without tangents V Shankar, A Fang, W Guo, S Fridovich-Keil, J Ragan-Kelley, L Schmidt, ... International Conference on Machine Learning, 8614-8623, 2020 | 79 | 2020 |
| Differentiable vector graphics rasterization for editing and learning TM Li, M Lukáč, M Gharbi, J Ragan-Kelley ACM Transactions on Graphics (TOG) 39 (6), 1-15, 2020 | 72 | 2020 |
| Gemmini: Enabling systematic deep-learning architecture evaluation via full-stack integration H Genc, S Kim, A Amid, A Haj-Ali, V Iyer, P Prakash, J Zhao, D Grubb, ... 2021 58th ACM/IEEE Design Automation Conference (DAC), 769-774, 2021 | 66 | 2021 |
Fredo DurandProfessor of Computer Science, MITZweryfikowany adres z mit.edu
