LayoutBench: Performance Benchmarking of Cloud Storage Layouts for Multimedia Data
Modern multimedia machine learning workloads increasingly store large-scale datasets in cloud object storage services such as AWS S3. How these samples are physically organized in storage (i.e.,storage layout) directly affects how quickly and cheaply they can be retrieved. Yet the benchmarks used to guide storage decisions today focus on database engines and query processing, and none systematically evaluates how different storage layouts perform for multimedia data retrieval. We present LayoutBench, the first benchmark designed to fill this gap. It evaluates three representative layout strategies: storing each sample as an individual object (L1), sequentially packing samples into tar arc...
| Authors | Debopam Sanyal, Hongjie Chen, Alexey Tumanov et al. |
|---|---|
| Primary category | cs.DC |
| Published | 30 July 2026 |
| Last updated at source | 30 July 2026 |
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