Scalable and Performant Data Loading
Project description
SPDL
SPDL (Scalable and Performant Data Loading) is a library and project to explore the design of performant data loading.
It provides flexible pipeline abstraction and a set of operations used for processing array data.
Documentation
Please checkout the documentation.
License
SPDL is BSD 2-Clause licensed, as found in the LICENSE file.
Citation
Please use the following BibTex for citing our project if you find it useful.
@misc{hira2025scalableperformantdataloading,
title={Scalable and Performant Data Loading},
author={Moto Hira and Christian Puhrsch and Valentin Andrei and Roman Malinovskyy and Gael Le Lan and Abhinandan Krishnan and Joseph Cummings and Miguel Martin and Gokul Gunasekaran and Yuta Inoue and Alex J Turner and Raghuraman Krishnamoorthi},
year={2025},
eprint={2504.20067},
archivePrefix={arXiv},
primaryClass={cs.DC},
url={https://arxiv.org/abs/2504.20067},
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file spdl-0.2.0-py3-none-any.whl.
File metadata
- Download URL: spdl-0.2.0-py3-none-any.whl
- Upload date:
- Size: 2.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c128cfc9875eac5f4e93daf9d04ebb4b9323631676d85968faede8c1858bcfd2
|
|
| MD5 |
ca7d30a624562dbc160bd6f7ca76de43
|
|
| BLAKE2b-256 |
55631095dd7d63675caf89390fac9f91e070fe47550d84b8ea561eb0a92e6069
|