The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format

Summary: Image Calculator: a self-designing image storage format that adapts to the AI task by exploring a large space of candidate formats with composite performance models. Outperforms JPEG variants with up to 14.2x faster inference and 8.2x storage reduction, with minimal accuracy loss, across diverse data, models, and hardware. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: hd9b77d880b1a368e
Venue: SIGMOD
Year: 2024
Pagerank: 5.0921006e-05
Overall Rank: 10,043 | 32.48%
DOI: 10.1145/3639307

Incoming Non-self Citations Over Time

Authors

1. Utku Sirin (Harvard University)
2. Stratos Idreos (Harvard University)

BibTeX Citation

@inproceedings{sirin_sigmod24,
        title = {{The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format}},
        author = {Sirin, Utku and Idreos, Stratos},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639307},
        url = {https://dl.acm.org/doi/10.1145/3639307},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,166	Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving	2025	SIGMOD	5.8631131e-05
8,620	Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines	2024	SIGMOD	5.301557e-05
9,987	Frequency-Store: Scaling Image AI by A Column-Store for Images	2025	CIDR	5.1001827e-05

Outgoing Citations (Sorted by Pagerank)

Showing 22 of 72 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
6,640	Dynamic Parameter Allocation in Parameter Servers	2020	VLDB	5.7251952e-05
6,662	UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads	2022	VLDB	5.7171651e-05
6,754	Agile and Accurate CTR Prediction Model Training for Massive-Scale Online Advertising Systems	2021	SIGMOD	5.6902479e-05
7,009	Video-zilla: An Indexing Layer for Large-Scale Video Analytics	2022	SIGMOD	5.6222568e-05
7,244	Serverless Data Science - Are We There Yet? A Case Study of Model Serving	2022	SIGMOD	5.5762915e-05
7,284	SeeSaw: Interactive Ad-hoc Search Over Image Databases	2023	SIGMOD	5.5664736e-05
7,538	Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines	2023	SIGMOD	5.4995874e-05
7,809	Nautilus: An Optimized System for Deep Transfer Learning over Evolving Training Datasets	2022	SIGMOD	5.4490255e-05
7,868	WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Model	2022	VLDB	5.4365239e-05
7,897	Using VDMS to Index and Search 100M Images	2021	VLDB	5.4317361e-05
7,915	Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems	2022	SIGMOD	5.4276987e-05
8,277	Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale	2022	VLDB	5.3639084e-05
8,620	Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines	2024	SIGMOD	5.301557e-05
8,812	FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement	2023	SIGMOD	5.2722828e-05
9,339	FEC: Efficient Deep Recommendation Model Training with Flexible Embedding Communication	2023	SIGMOD	5.1910676e-05
9,457	COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression	2022	VLDB	5.1735029e-05
9,539	Controlled Intentional Degradation in Analytical Video Systems	2022	SIGMOD	5.1621607e-05
9,711	Serenade - Low-Latency Session-Based Recommendation in e-Commerce at Scale	2022	SIGMOD	5.1371426e-05
10,013	ETO: Accelerating Optimization of DNN Operators by High-Performance Tensor Program Reuse	2022	VLDB	5.0971861e-05
10,340	Classifier Construction Under Budget Constraints	2022	SIGMOD	5.0167904e-05
10,341	Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training	2022	VLDB	5.0167904e-05
10,342	Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates	2022	VLDB	5.0167904e-05

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