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Jared Roesch
Jared Roesch
OctoML Inc
cs.uw.edu의 이메일 확인됨 - 홈페이지
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A hardware–software blueprint for flexible deep learning specialization
T Moreau, T Chen, L Vega, J Roesch, E Yan, L Zheng, J Fromm, Z Jiang, ...
IEEE Micro 39 (5), 8-16, 2019
1732019
Relay: A new ir for machine learning frameworks
J Roesch, S Lyubomirsky, L Weber, J Pollock, M Kirisame, T Chen, ...
Proceedings of the 2nd ACM SIGPLAN international workshop on machine …, 2018
1242018
A metaprogramming framework for formal verification
G Ebner, S Ullrich, J Roesch, J Avigad, L de Moura
Proceedings of the ACM on Programming Languages 1 (ICFP), 1-29, 2017
1172017
Fuzzing the Rust typechecker using CLP (T)
K Dewey, J Roesch, B Hardekopf
2015 30th IEEE/ACM International Conference on Automated Software …, 2015
882015
Dynamic tensor rematerialization
M Kirisame, S Lyubomirsky, A Haan, J Brennan, M He, J Roesch, T Chen, ...
arXiv preprint arXiv:2006.09616, 2020
782020
Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries
S Chu, B Murphy, J Roesch, A Cheung, D Suciu
arXiv preprint arXiv:1802.02229, 2018
662018
Language fuzzing using constraint logic programming
K Dewey, J Roesch, B Hardekopf
Proceedings of the 29th ACM/IEEE international conference on Automated …, 2014
572014
Nimble: Efficiently compiling dynamic neural networks for model inference
H Shen, J Roesch, Z Chen, W Chen, Y Wu, M Li, V Sharma, Z Tatlock, ...
Proceedings of Machine Learning and Systems 3, 208-222, 2021
442021
Tea: A high-level language and runtime system for automating statistical analysis
E Jun, M Daum, J Roesch, S Chasins, E Berger, R Just, K Reinecke
Proceedings of the 32nd Annual ACM Symposium on User Interface Software and …, 2019
402019
Improved type specialization for dynamic scripting languages
MN Kedlaya, J Roesch, B Robatmili, M Reshadi, B Hardekopf
Proceedings of the 9th Symposium on Dynamic Languages, 37-48, 2013
342013
Relay: A high-level compiler for deep learning
J Roesch, S Lyubomirsky, M Kirisame, L Weber, J Pollock, L Vega, ...
arXiv preprint arXiv:1904.08368, 2019
262019
Bring your own codegen to deep learning compiler
Z Chen, CH Yu, T Morris, J Tuyls, YH Lai, J Roesch, E Delaye, V Sharma, ...
arXiv preprint arXiv:2105.03215, 2021
152021
Theia: automatically generating correct program state visualizations
J Pollock, J Roesch, D Woos, Z Tatlock
Proceedings of the 2019 ACM SIGPLAN Symposium on SPLASH-E, 46-56, 2019
112019
Relay: A high-level IR for deep learning
J Roesch, S Lyubomirsky, M Kirisame, J Pollock, L Weber, Z Jiang, ...
arXiv preprint arXiv:1904.08368, 2019
112019
Automated data structure generation: Refuting common wisdom
K Dewey, L Nichols, B Hardekopf
2015 IEEE/ACM 37th IEEE International Conference on Software Engineering 1 …, 2015
102015
An architecture supporting formal and compositional binary analysis
J McMahan, M Christensen, L Nichols, J Roesch, SY Guo, B Hardekopf, ...
ACM SIGARCH Computer Architecture News 45 (1), 177-191, 2017
92017
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning
R Lai, J Shao, S Feng, SS Lyubomirsky, B Hou, W Lin, Z Ye, H Jin, Y Jin, ...
arXiv preprint arXiv:2311.02103, 2023
42023
Optimizing machine learning models
M Welsh, J Knight, J Roesch, T Moreau, A Chang, T Chen, LH Ceze, ...
US Patent 11,216,752, 2022
32022
LastLayer: Toward hardware and software continuous integration
L Vega, J Roesch, J McMahan, L Ceze
IEEE Micro 40 (4), 103-111, 2020
32020
Principled Optimization of Dynamic Neural Networks
J Roesch
University of Washington, 2020
22020
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