Peter Bodík

Affiliations:
  • University of California, Berkeley, USA


According to our database1, Peter Bodík authored at least 32 papers between 2004 and 2024.

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Bibliography

2024
Evaluating how interactive visualizations can assist in finding samples where and how computer vision models make mistakes.
Proceedings of the 17th IEEE Pacific Visualization Conference, 2024

2023
Where does a computer vision model make mistakes? Using interactive visualizations to find where and how CV models can improve.
CoRR, 2023

2018
Unified Management and Optimization of Edge-Cloud IoT Applications.
CoRR, 2018

Focus: Querying Large Video Datasets with Low Latency and Low Cost.
CoRR, 2018

Chameleon: scalable adaptation of video analytics.
Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, 2018

Focus: Querying Large Video Datasets with Low Latency and Low Cost.
Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation, 2018

Steel: Simplified Development and Deployment of Edge-Cloud Applications.
Proceedings of the 10th USENIX Workshop on Hot Topics in Cloud Computing, 2018

VideoEdge: Processing Camera Streams using Hierarchical Clusters.
Proceedings of the 2018 IEEE/ACM Symposium on Edge Computing, 2018

2017
Real-Time Video Analytics: The Killer App for Edge Computing.
Computer, 2017

Live Video Analytics at Scale with Approximation and Delay-Tolerance.
Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, 2017

Demo: Live Video Stream Triggers.
Proceedings of the 15th Annual International Conference on Mobile Systems, 2017

Distributed resource management across process boundaries.
Proceedings of the 2017 Symposium on Cloud Computing, SoCC 2017, Santa Clara, CA, USA, 2017

2016
2DFQ: Two-Dimensional Fair Queuing for Multi-Tenant Cloud Services.
Proceedings of the ACM SIGCOMM 2016 Conference, Florianopolis, Brazil, August 22-26, 2016, 2016

2015
Low Latency Geo-distributed Data Analytics.
Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication, 2015

Network-Aware Scheduling for Data-Parallel Jobs: Plan When You Can.
Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication, 2015

Retro: Targeted Resource Management in Multi-tenant Distributed Systems.
Proceedings of the 12th USENIX Symposium on Networked Systems Design and Implementation, 2015

2014
Brief announcement: deadline-aware scheduling of big-data processing jobs.
Proceedings of the 26th ACM Symposium on Parallelism in Algorithms and Architectures, 2014

Towards General-Purpose Resource Management in Shared Cloud Services.
Proceedings of the 10th Workshop on Hot Topics in System Dependability, 2014

2013
Speeding up distributed request-response workflows.
Proceedings of the ACM SIGCOMM 2013 Conference, 2013

Virtualizing Traffic Shapers for Practical Resource Allocation.
Proceedings of the 5th USENIX Workshop on Hot Topics in Cloud Computing, 2013

2012
Surviving failures in bandwidth-constrained datacenters.
Proceedings of the ACM SIGCOMM 2012 Conference, 2012

Jockey: guaranteed job latency in data parallel clusters.
Proceedings of the European Conference on Computer Systems, 2012

2011
Overview of the workshop on managing large-scale systems via the analysis of system logs and the application of machine learning techniques.
ACM SIGOPS Oper. Syst. Rev., 2011

The SCADS Director: Scaling a Distributed Storage System Under Stringent Performance Requirements.
Proceedings of the 9th USENIX Conference on File and Storage Technologies, 2011

2010
Automating Datacenter Operations Using Machine Learning.
PhD thesis, 2010

Fingerprinting the datacenter: automated classification of performance crises.
Proceedings of the European Conference on Computer Systems, 2010

Characterizing, modeling, and generating workload spikes for stateful services.
Proceedings of the 1st ACM Symposium on Cloud Computing, 2010

2009
Automatic exploration of datacenter performance regimes.
Proceedings of the 1st Workshop on Automated Control for Datacenters and Clouds, 2009

Statistical Machine Learning Makes Automatic Control Practical for Internet Datacenters.
Proceedings of the Workshop on Hot Topics in Cloud Computing, 2009

2008
HiLighter: Automatically Building Robust Signatures of Performance Behavior for Small- and Large-Scale Systems.
Proceedings of the Third Workshop on Tackling Computer Systems Problems with Machine Learning Techniques, 2008

2005
Combining Visualization and Statistical Analysis to Improve Operator Confidence and Efficiency for Failure Detection and Localization.
Proceedings of the Second International Conference on Autonomic Computing (ICAC 2005), 2005

2004
Distributed regression: an efficient framework for modeling sensor network data.
Proceedings of the Third International Symposium on Information Processing in Sensor Networks, 2004


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