Projects available for funding

• Jupyter Ecosystem

  Modernizing nbconvert

  Conversion of Jupyter notebooks to PDF currently relies on nbconvert in the backend, which in turns uses a headless browser for producing the PDF. We propose to…

  30 000 €

  0% funded
• Jupyter Ecosystem

  Raster processing tools in JupyterGIS

  JupyterGIS currently offers a set of vector processing and conversion tools. These capabilities are powered by a GDAL WebAssembly (WASM) build running in the br…

  TBD

  0% funded
• Jupyter Ecosystem

  Bringing processing tools to the JupyterGIS Python API

  JupyterGIS currently supports several vector processing and conversion tools, currently available only through the JupyterGIS user interface. We plan to extend …

  10 000 €

  0% funded
• Package Management

  Package requests for emscripten-forge

  Emscripten-forge is a conda package distribution specifically designed for WebAssembly. While the number of available emscripten-forge packages is growing quick…

  TBD

  0% funded
• Scientific Computing

  SVE2 support in xsimd

  xsimd is a C++ scientific library that abstracts low-level high performances computing primitives across different hardwares. We will add support for the latest…

  30 000 €

  0% funded
• Scientific Computing

  Float16 support in xsimd

  xsimd is a C++ scientific library that abstracts low-level high performances computing primitives across different hardwares. We will add vectorized support for…

  20 000 €

  0% funded
• Scientific Computing

  Implementing Kazushige Goto Algorithms for Matrix Operations in xtensor

  This project aims to integrate Kazushige Goto’s highly optimized matrix multiplication algorithms into the xtensor framework, leveraging the xsimd library for S…

  45 000 €

  0% funded
• Apache Arrow and Parquet

  Complete BinaryView / StringView support in Arrow C++

  BinaryView is a more recent and more efficient alternative to Arrow's standard Binary type. It allows for inlined storage of short strings and fast prefix compa…

  TBD

  0% funded
• Apache Arrow and Parquet

  Complete Decimal32 / Decimal64 support in Arrow C++

  Decimal32 and Decimal64 are more compact and computationally more efficient data types than the standard Decimal128.

  TBD

  0% funded
• Apache Arrow and Parquet

  Complete Float16 support in Arrow C++

  Float16 is a more compact data type than Float32 and Float64, and sees growing usage in applications where its limited precision is sufficient.

  TBD

  0% funded
• Apache Arrow and Parquet

  Complete Run-End-Encoded support in Arrow C++

  Like dictionary encoding, run-end-encoding allows representing some kinds of data more efficiently.

  TBD

  0% funded
• Apache Arrow and Parquet

  Parquet reader optimizations

  Converting Parquet optional values to nullable Arrow data is often a performance bottleneck. We will optimize that step for the most common cases.

  TBD

  0% funded