Daniel Crankshaw

20 papers A* 2A 2B 1Misc 3Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Enhancing Network Failure Mitigation with Performance-Aware Ranking. NSDI Pooria Namyar, Arvin Ghavidel, Daniel Crankshaw, Daniel S. Berger, Kevin Hsieh, Srikanth Kandula, Ramesh Govindan, Behnaz Arzani
2024	Misc	`conf`	Solving Max-Min Fair Resource Allocations Quickly on Large Graphs. NSDI Pooria Namyar, Behnaz Arzani, Srikanth Kandula, Santiago Segarra, Daniel Crankshaw, Umesh Krishnaswamy, Ramesh Govindan, Himanshu Raj
2023	J	`jnl`	Mitigating the Performance Impact of Network Failures in Public Clouds. CoRR Pooria Namyar, Behnaz Arzani, Daniel Crankshaw, Daniel S. Berger, Kevin Hsieh, Srikanth Kandula, Ramesh Govindan
2023	J	`jnl`	Solving Max-Min Fair Resource Allocations Quickly on Large Graphs. CoRR Pooria Namyar, Behnaz Arzani, Srikanth Kandula, Santiago Segarra, Daniel Crankshaw, Umesh Krishnaswamy, Ramesh Govindan, Himanshu Raj
2022	J	`jnl`	SOL: Safe On-Node Learning in Cloud Platforms. CoRR Yawen Wang, Daniel Crankshaw, Neeraja J. Yadwadkar, Daniel S. Berger, Christos Kozyrakis, Ricardo Bianchini
2022	A*	`conf`	SOL: safe on-node learning in cloud platforms. ASPLOS Yawen Wang, Daniel Crankshaw, Neeraja J. Yadwadkar, Daniel S. Berger, Christos Kozyrakis, Ricardo Bianchini
2020	—	`conf`	InferLine: latency-aware provisioning and scaling for prediction serving pipelines. SoCC Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, Alexey Tumanov
2019	—	`—`	The Design and Implementation of Low-Latency Prediction Serving Systems. Daniel Crankshaw
2018	A	`conf`	IDK Cascades: Fast Deep Learning by Learning not to Overthink. UAI Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Fisher Yu, Joseph E. Gonzalez
2018	J	`jnl`	InferLine: ML Inference Pipeline Composition Framework. CoRR Daniel Crankshaw, Gur-Eyal Sela, Corey Zumar, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov
2018	J	`jnl`	Research for practice: prediction-serving systems. Commun. ACM Daniel Crankshaw, Joseph Gonzalez, Peter Bailis
2017	Misc	`conf`	Clipper: A Low-Latency Online Prediction Serving System. NSDI Daniel Crankshaw, Xin Wang, Giulio Zhou, Michael J. Franklin, Joseph E. Gonzalez, Ion Stoica
2017	J	`jnl`	Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning. CoRR Richard Liaw, Sanjay Krishnan, Animesh Garg, Daniel Crankshaw, Joseph E. Gonzalez, Ken Goldberg
2017	J	`jnl`	IDK Cascades: Fast Deep Learning by Learning not to Overthink. CoRR Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Joseph E. Gonzalez
2016	J	`jnl`	Clipper: A Low-Latency Online Prediction Serving System. CoRR Daniel Crankshaw, Xin Wang, Giulio Zhou, Michael J. Franklin, Joseph E. Gonzalez, Ion Stoica
2015	A	`conf`	The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox. CIDR Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan
2014	A*	`conf`	GraphX: Graph Processing in a Distributed Dataflow Framework. OSDI Joseph E. Gonzalez, Reynold S. Xin, Ankur Dave, Daniel Crankshaw, Michael J. Franklin, Ion Stoica
2014	J	`jnl`	GraphX: Unifying Data-Parallel and Graph-Parallel Analytics. CoRR Reynold S. Xin, Daniel Crankshaw, Ankur Dave, Joseph E. Gonzalez, Michael J. Franklin, Ion Stoica
2014	J	`jnl`	The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox. CoRR Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan
2013	B	`conf`	Inverted indices for particle tracking in petascale cosmological simulations. SSDBM Daniel Crankshaw, Randal C. Burns, Bridget Falck, Tamas Budavari, Alexander S. Szalay, Jie Wang