| Graphx: Graph processing in a distributed dataflow framework JE Gonzalez, RS Xin, A Dave, D Crankshaw, MJ Franklin, I Stoica 11th {USENIX} Symposium on Operating Systems Design and Implementation …, 2014 | 1059 | 2014 |
| Clipper: A low-latency online prediction serving system D Crankshaw, X Wang, G Zhou, MJ Franklin, JE Gonzalez, I Stoica 14th {USENIX} Symposium on Networked Systems Design and Implementation …, 2017 | 235 | 2017 |
| Graphx: Unifying data-parallel and graph-parallel analytics RS Xin, D Crankshaw, A Dave, JE Gonzalez, MJ Franklin, I Stoica arXiv preprint arXiv:1402.2394, 2014 | 102 | 2014 |
| The missing piece in complex analytics: Low latency, scalable model management and serving with velox D Crankshaw, P Bailis, JE Gonzalez, H Li, Z Zhang, MJ Franklin, A Ghodsi, ... arXiv preprint arXiv:1409.3809, 2014 | 92 | 2014 |
| Idk cascades: Fast deep learning by learning not to overthink X Wang, Y Luo, D Crankshaw, A Tumanov, F Yu, JE Gonzalez arXiv preprint arXiv:1706.00885, 2017 | 39 | 2017 |
| Inferline: ML inference pipeline composition framework D Crankshaw, GE Sela, C Zumar, X Mo, JE Gonzalez, I Stoica, ... arXiv preprint arXiv:1812.01776, 2018 | 21 | 2018 |
| Composing meta-policies for autonomous driving using hierarchical deep reinforcement learning R Liaw, S Krishnan, A Garg, D Crankshaw, JE Gonzalez, K Goldberg arXiv preprint arXiv:1711.01503, 2017 | 11 | 2017 |
| Context: The missing piece in the machine learning lifecycle R Garcia, V Sreekanti, N Yadwadkar, D Crankshaw, JE Gonzalez, ... KDD CMI Workshop 114, 2018 | 9 | 2018 |
| Scalable training and serving of personalized models D Crankshaw, X Wang, JE Gonzalez, MJ Franklin NIPS 2015 Workshop on Machine Learning Systems (LearningSys), 2015 | 7 | 2015 |
| Inverted indices for particle tracking in petascale cosmological simulations D Crankshaw, R Burns, B Falck, T Budavári, AS Szalay, J Wang Proceedings of the 25th International Conference on Scientific and …, 2013 | 4 | 2013 |
| GraphX: graph processing in a distributed dataflow framework Mark JE Gonzalez, RS Xin, A Dave, D Crankshaw, MJ Franklin, I Stoica | 2 | 2014 |
| The missing piece in complex analytics: Low latency, scalable model management and serving with velox. CIDR, 2015. Supplementary Material A Example algorithm implementation … D Crankshaw, P Bailis, JE Gonzalez, H Li, Z Zhang, MJ Franklin, A Ghodsi, ... | 2 | 2014 |
| InferLine: latency-aware provisioning and scaling for prediction serving pipelines D Crankshaw, GE Sela, X Mo, C Zumar, I Stoica, J Gonzalez, A Tumanov Proceedings of the 11th ACM Symposium on Cloud Computing, 477-491, 2020 | 1 | 2020 |
| The Indra Simulation Database B Falck, T Budavari, S Cole, D Crankshaw, L Dobos, G Lemson, ... American Astronomical Society Meeting Abstracts# 218 218, 131.04, 2011 | 1 | 2011 |
| The Design and Implementation of Low-Latency Prediction Serving Systems D Crankshaw UC Berkeley, 2019 | | 2019 |
| InferLine: ML Prediction Pipeline Provisioning and Management for Tight Latency Objectives D Crankshaw, GE Sela, C Zumar, X Mo, JE Gonzalez, I Stoica, ... arXiv preprint arXiv:1812.01776, 2018 | | 2018 |
| Database Architecture for the Indra Cosmological Simulations DS Crankshaw, B Falck, T Budavari, L Dobos, G Lemson, M Neyrinck, ... American Astronomical Society Meeting Abstracts# 219 219, 145.13, 2012 | | 2012 |
