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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
12294
Venue
VLDB
Year
2020
Pagerank
0.00011924049
Overall Rank
1,157 | 92.07%
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 26 of 26 citing papers.

Rank Citing Paper Year Venue Pagerank
1,446 Analyzing and Mitigating Data Stalls in DNN Training 2021 VLDB 0.0001076818
2,273 SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging 2021 SIGMOD 8.8230899e-05
3,272 VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition 2021 VLDB 7.5775321e-05
4,067 Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches 2021 VLDB 6.9293511e-05
5,003 Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism 2023 VLDB 6.4065691e-05
5,839 Doing More with Less: Characterizing Dataset Downsampling for AutoML 2021 VLDB 6.0699037e-05
6,339 In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle 2022 SIGMOD 5.907165e-05
6,538 UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads 2022 VLDB 5.8477764e-05
6,588 Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines 2023 VLDB 5.833338e-05
7,232 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 5.6659017e-05
7,656 Nautilus: An Optimized System for Deep Transfer Learning over Evolving Training Datasets 2022 SIGMOD 5.5740571e-05
8,244 SHiFT: An Efficient, Flexible Search Engine for Transfer Learning 2023 VLDB 5.4587712e-05
8,905 TensorSocket: Shared Data Loading for Deep Learning Training 2026 SIGMOD 5.3483178e-05
8,979 Cerebro: A Layered Data Platform for Scalable Deep Learning 2021 CIDR 5.3399615e-05
9,290 Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale 2022 VLDB 5.2910774e-05
9,292 COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression 2022 VLDB 5.2908632e-05
9,371 Towards an Optimized GROUP BY Abstraction for Large-Scale Machine Learning 2021 VLDB 5.275595e-05
9,372 Intermittent Human-in-the-Loop Model Selection using Cerebro: A Demonstration 2021 VLDB 5.275595e-05
9,881 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 5.2040783e-05
11,066 ML-Asset Management: Curation, Discovery, and Utilization 2025 VLDB 5.093636e-05
11,209 Database Native Model Selection: Harnessing Deep Neural Networks in Database Systems 2024 VLDB 5.093636e-05
11,537 Redundancy Elimination in Distributed Matrix Computation 2022 SIGMOD 5.093636e-05
11,629 Ease.ML: A Lifecycle Management System for MLDev and MLOps 2021 CIDR 5.093636e-05
11,645 Grouped Learning: Group-By Model Selection Workloads 2021 SIGMOD 5.093636e-05
13,375 Reimagining Deep Learning Systems Through the Lens of Data Systems 2024 VLDB -
13,473 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
106 The MADlib Analytics Library or MAD Skills, the SQL 2012 VLDB 0.00033539462
518 Towards a Unified Architecture for in-RDBMS Analytics 2012 SIGMOD 0.00017167492
1,079 Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML 2014 VLDB 0.00012258469
1,250 Data Management in Machine Learning: Challenges, Techniques, and Systems 2017 SIGMOD 0.00011485301
2,162 Heterogeneity-aware Distributed Parameter Servers 2017 SIGMOD 9.0581831e-05
2,693 FlexPS: Flexible Parallelism Control in Parameter Server Architecture 2018 VLDB 8.247004e-05
2,987 Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations 2019 SIGMOD 7.8907997e-05
3,459 A Comparative Evaluation of Systems for Scalable Linear Algebra-based Analytics 2018 VLDB 7.3953716e-05
3,573 VISTA: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale 2020 SIGMOD 7.2977194e-05
3,782 CROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers 2019 VLDB 7.1298979e-05
5,362 Mariana: Tencent Deep Learning Platform and its Applications 2014 VLDB 6.2481421e-05
6,485 Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent 2019 SIGMOD 5.8657457e-05
13,473 Errata for "Cerebro: A Data System for Optimized Deep Learning Model Selection" 2021 VLDB -
13,514 Demonstration of Krypton: Optimized CNN Inference for Occlusion-based Deep CNN Explanations 2019 VLDB -
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