Jonathan Ragan-Kelley
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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
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
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
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
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
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
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
Darkroom: compiling high-level image processing code into hardware pipelines.
J Hegarty, JS Brunhaver, Z DeVito, J Ragan-Kelley, N Cohen, S Bell, ...
ACM Trans. Graph. 33 (4), 144:1-144:11, 2014
OpenFab: A Programmable Pipeline for Multimaterial Fabrication
K Vidimče, SP Wang, J Ragan-Kelley, W Matusik
Communications of the ACM 62 (9), 97-105, 2019
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
Differentiable vector graphics rasterization for editing and learning
TM Li, M LukŠč, M Gharbi, J Ragan-Kelley
ACM Transactions on Graphics (TOG) 39 (6), 1-15, 2020
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
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
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
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
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
Portable performance on heterogeneous architectures
PM Phothilimthana, J Ansel, J Ragan-Kelley, S Amarasinghe
ACM SIGARCH Computer Architecture News 41 (1), 431-444, 2013
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
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
Proximal: Efficient image optimization using proximal algorithms
F Heide, S Diamond, M NieŖner, J Ragan-Kelley, W Heidrich, G Wetzstein
ACM Transactions on Graphics (TOG) 35 (4), 1-15, 2016
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