Cerebro: A Layered Data Platform for Scalable Deep Learning

Summary: Cerebro: a layered data platform that makes DL model selection a first-class data-management problem with higher-level APIs and a DB-inspired architecture for coordinated large-scale model/hyperparameter search. Uses multi-query optimization to share computation and reduce resource waste. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: ha6b29a81644119f9
Venue: CIDR
Year: 2021
Pagerank: 5.2201471e-05
Overall Rank: 9,144 | 38.53%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Arun Kumar (University of California San Diego)
2. Supun Nakandala (University of California San Diego)
3. Yuhao Zhang (University of California San Diego)
4. Side Li (University of California San Diego)
5. Advitya Gemawat (University of California San Diego)
6. Kabir Nagrecha (University of California San Diego)

BibTeX Citation

@inproceedings{kumar_cidr21,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '21},
        title = {{Cerebro: A Layered Data Platform for Scalable Deep Learning}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Kumar, Arun and Nakandala, Supun and Zhang, Yuhao and Li, Side and Gemawat, Advitya and Nagrecha, Kabir},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,095	Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches	2021	VLDB	6.8095767e-05
5,899	Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines	2023	VLDB	5.9545431e-05
7,069	Saturn: An Optimized Data System for Multi-Large-Model Deep Learning Workloads	2024	VLDB	5.6083188e-05
9,393	GraphGem: Optimized Scalable System for Graph Convolutional Networks	2021	SIGMOD	5.1860604e-05
9,556	Towards an Optimized GROUP BY Abstraction for Large-Scale Machine Learning	2021	VLDB	5.1572248e-05
9,557	Intermittent Human-in-the-Loop Model Selection using Cerebro: A Demonstration	2021	VLDB	5.1572248e-05
9,900	Scalable Graph Convolutional Network Training on Distributed-Memory Systems	2023	VLDB	5.1116429e-05
11,532	StarfishDB: a Query Execution Engine for Relational Probabilistic Programming	2024	SIGMOD	4.9793485e-05
11,952	Grouped Learning: Group-By Model Selection Workloads	2021	SIGMOD	4.9793485e-05
13,689	Reimagining Deep Learning Systems Through the Lens of Data Systems	2024	VLDB	-

Outgoing Citations (Sorted by Pagerank)

Showing 20 of 20 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
105	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00033638251
503	Towards a Unified Architecture for in-RDBMS Analytics	2012	SIGMOD	0.00017202276
522	PyTorch Distributed: Experiences on Accelerating Data Parallel Training	2020	VLDB	0.00016912378
654	Materialization Optimizations for Feature Selection Workloads	2014	SIGMOD	0.0001510357
730	Learning Generalized Linear Models Over Normalized Data	2015	SIGMOD	0.00014406936
1,152	Cerebro: A Data System for Optimized Deep Learning Model Selection	2020	VLDB	0.00011801961
1,255	Data Management in Machine Learning: Challenges, Techniques, and Systems	2017	SIGMOD	0.00011325762
1,256	Towards Linear Algebra over Normalized Data	2017	VLDB	0.00011314687
2,199	Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra	2019	SIGMOD	8.8750296e-05
2,586	Brainwash: A Data System for Feature Engineering	2013	CIDR	8.2560072e-05
2,710	Panorama: A Data System for Unbounded Vocabulary Querying over Video	2020	VLDB	8.1041775e-05
3,040	Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations	2019	SIGMOD	7.7216143e-05
3,518	A Comparative Evaluation of Systems for Scalable Linear Algebra-based Analytics	2018	VLDB	7.2400627e-05
3,630	VISTA: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale	2020	SIGMOD	7.1496182e-05
4,095	Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches	2021	VLDB	6.8095767e-05
5,682	Demonstration of Santoku: Optimizing Machine Learning over Normalized Data	2015	VLDB	6.0397904e-05
6,592	Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent	2019	SIGMOD	5.7421684e-05
7,536	Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System	2013	VLDB	5.5002435e-05
8,747	Probabilistic Management of OCR Data using an RDBMS	2012	VLDB	5.2865969e-05
13,827	Demonstration of Krypton: Optimized CNN Inference for Occlusion-based Deep CNN Explanations	2019	VLDB	-

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