.. DLIO documentation master file Deep Learning I/O Benchmark =============================================================== Deep Learning I/O (`DLIO`) Benchmark is a benchmark suite aiming at emulating the I/O pattern and behavior of deep learning applications. The benchmark is delivered as an executable that can be configured for various deep learning workloads. It uses a modular design to incorporate different data loaders, data formats, dataset organizations, and use training configuration parameters similar to the actual deep learning applications. It is able to represent the I/O process of a broad spectrum of deep leanrning applications. The main features of `DLIO` include: * Easy-to-use configuration through YAML files which represent the I/O process of different deep learing applications. * Easy-to-use data generator capable to generate synthetic datasets of different formats, different data organizations and layouts. * Full transparency over emulation of I/O access with logging and profiling at different levels with DFTracer. * Supporting emulating both sequential training and distributed data parallel training. GitHub repo: https://github.com/argonne-lcf/dlio_benchmark. ================================== .. toctree:: :maxdepth: 1 :caption: Overview overview .. toctree:: :maxdepth: 1 :caption: Getting Started install config run examples .. toctree:: :maxdepth: 1 :caption: Custom data loader and reader plugins custom_data_loader custom_reader custom_checkpointing_mechanism .. toctree:: :maxdepth: 1 :caption: Tested systems and Known issues testedsystems instructions_lassen knownissues .. toctree:: :maxdepth: 1 :caption: How to contribute contribute .. toctree:: :maxdepth: 1 :caption: Resources resources .. toctree:: :maxdepth: 1 :caption: Acknowdgments acknowledgments .. toctree:: :maxdepth: 1 :caption: Appendix jpeg_generator profiling .. toctree:: :maxdepth: 1 :caption: Legal copyright license Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search`