Juliacon 2024

Fabian Gans

I am a physicist by training and am currently studying Global Biogeochemical Cycles in the Earth System using Remote Sensing, Meteorological and other data sets based at the Max-Planck-Institute for Biogeochemistry, Jena, Germany.
My first commit to my first Julia package dates back to the year 2012 and since then I have authored and contributed to packages in the Julia Geodata and processing ecosystem, examples are NetCDF.jl, Zarr.jl, DiskArrays.jl, YAXArrays.jl EarthDataLab.jl and others. Some may know me under my github tag @meggart


Sessions

07-10
14:30
5min
Scientific Data Minisymposium
Mark Kittisopikul, Ph.D., Fabian Gans

Julia's elegance and speed lends itself to applications in scientific computing that requires a strong scientific data ecosystem. Building upon prior successful minisymposia on tabular data, the Scientific Data minisymposium will extend the scope to dealing with annotated, hiearchical, and n-dimensional data. Additionally, the symposium will invite talks on processing large datasets using advanced chunking techniques, distribution of big data via cloud computing and data formats.

Scientific Data Minisymposium
Function (4.1)
07-10
14:35
30min
DiskArrays.jl for working with large disk-based nd-arrays
Fabian Gans, Felix Cremer

DiskArrays.jl provides the AbstractDiskArray interface for chunked and compressed n-dimensional arrays with slow random access. Implementing the interface gives access to a wide set of indexing, views, reductions and broadcasting. Downstream packages can optimize parallel operations on these chunked arrays using the AbstractDiskArray interface.

Scientific Data Minisymposium
Function (4.1)
07-10
15:05
10min
PyramidScheme.jl overviews for larger than memory arrays
Felix Cremer, Fabian Gans

PyramidScheme.jl is a package to easily and efficiently compute pyramids of an array which might be larger than RAM.
PyramidScheme.jl provides the Pyramid struct to handle the layers of a pyramid.
A pyramid is a collection of subarrays of a larger array so that every layer is half the size in every dimension so that pixels are combined to get to the next level of the pyramid.
These different layers allow to lazily give an overview of the data without having to load the whole array into memory.

Scientific Data Minisymposium
Function (4.1)