Event Details:
If your research uses data for computation, you should probably be using HDF5!
Hierarchical Data Format, version 5 (HDF5) is a high performance, very portable, self-describing data format, designed by and built for research computing. HDF5 features fast IO, and is an excellent way to organize and consolidate your research data into a handful of easy to manage file objects. HDF5 files are cross-platform portable, feature fast IO, and support unlimited collection sizes.
If your research produces (or requires as inputs) lots of directories and small data files, HDF5 can significantly improve your compute performance. Most importantly, HDF5 is easy to use!
This workshop will focus on implementation in Python, but the general principles apply across multiple platforms.