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Cerebro: A Data System for Optimized Deep Learning Model Selection

Summary: Cerebro is a data system for optimized deep-learning model selection, boosting throughput and reproducibility at lower cost. Model hopper parallelism, a hybrid task/data-parallel SGD, yields 3–10x speedups and memory/network savings across varied resources. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hd8941b74afeb7d78
Venue
VLDB
Year
2020
Pagerank
0.00011801961
Overall Rank
1,152 | 92.26%
DOI
10.14778/3407790.3407816

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{nakandala_vldb20,
        title = {{Cerebro: A Data System for Optimized Deep Learning Model Selection}},
        author = {Nakandala, Supun and Zhang, Yuhao and Kumar, Arun},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {11},
        pages = {2159--2173},
        doi = {10.14778/3407790.3407816},
        url = {https://doi.org/10.14778/3407790.3407816},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 27 of 27 citing papers.

Rank Citing Paper Year Venue Pagerank
1,475 Analyzing and Mitigating Data Stalls in DNN Training 2021 VLDB 0.00010556672
2,326 SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging 2021 SIGMOD 8.6309237e-05
3,331 VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition 2021 VLDB 7.4166095e-05
4,095 Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches 2021 VLDB 6.8095767e-05
5,009 Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism 2023 VLDB 6.3158866e-05
5,572 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 6.0802555e-05
5,899 Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines 2023 VLDB 5.9545431e-05
5,933 Doing More with Less: Characterizing Dataset Downsampling for AutoML 2021 VLDB 5.942188e-05
6,458 In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle 2022 SIGMOD 5.7773842e-05
6,662 UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads 2022 VLDB 5.7171651e-05
7,809 Nautilus: An Optimized System for Deep Transfer Learning over Evolving Training Datasets 2022 SIGMOD 5.4490255e-05
8,277 Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale 2022 VLDB 5.3639084e-05
8,411 SHiFT: An Efficient, Flexible Search Engine for Transfer Learning 2023 VLDB 5.336291e-05
9,067 TensorSocket: Shared Data Loading for Deep Learning Training 2026 SIGMOD 5.2283159e-05
9,144 Cerebro: A Layered Data Platform for Scalable Deep Learning 2021 CIDR 5.2201471e-05
9,457 COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression 2022 VLDB 5.1735029e-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
10,043 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 5.0921006e-05
10,798 NeurIDA: Dynamic Modeling for Effective In-Database Analytics 2026 VLDB 4.9793485e-05
11,426 ML-Asset Management: Curation, Discovery, and Utilization 2025 VLDB 4.9793485e-05
11,549 Database Native Model Selection: Harnessing Deep Neural Networks in Database Systems 2024 VLDB 4.9793485e-05
11,846 Redundancy Elimination in Distributed Matrix Computation 2022 SIGMOD 4.9793485e-05
11,936 Ease.ML: A Lifecycle Management System for MLDev and MLOps 2021 CIDR 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 -
13,787 Errata for "Cerebro: A Data System for Optimized Deep Learning Model Selection" 2021 VLDB -
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 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
1,081 Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML 2014 VLDB 0.00012123917
1,255 Data Management in Machine Learning: Challenges, Techniques, and Systems 2017 SIGMOD 0.00011325762
2,184 Heterogeneity-aware Distributed Parameter Servers 2017 SIGMOD 8.8958335e-05
2,725 FlexPS: Flexible Parallelism Control in Parameter Server Architecture 2018 VLDB 8.090861e-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
3,764 CROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers 2019 VLDB 7.0394265e-05
5,469 Mariana: Tencent Deep Learning Platform and its Applications 2014 VLDB 6.1183403e-05
6,592 Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent 2019 SIGMOD 5.7421684e-05
13,787 Errata for "Cerebro: A Data System for Optimized Deep Learning Model Selection" 2021 VLDB -
13,827 Demonstration of Krypton: Optimized CNN Inference for Occlusion-based Deep CNN Explanations 2019 VLDB -
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