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This document is under construction. Nothing is nailed in stone. Please commit changes, send pull-requests or create issues.

Let's make this a truly community-driven project by writing the roadmap together.

Roadmap clEsperanto


Mission of the clEsperanto project is to unite sub-communities of scientific image analysis by bridging between programming languages and environments.

  1. We aim crafting an easily accessible image processing library.
  2. We aim making image processing accessible for
    1. beginners and experts,
    2. programmers of any major language,
    3. users of any major operating system and
    4. owners of any major CPU and GPU hardware.
  3. We aim writing easy to read, maintain and extend code.
  4. We aim documenting our platform in an easily accessible way.
  5. We aim forming a community where users and developers make decisions together.


To achieve our goals, we plan to adapt the CLIJ project to be accessible to a broader audience.

Major tasks

  1. Core development: Translating ClearCL to C++ and wrapping from Python/Java/...
    1. CLIc via OpenCL C++ Wrapper API
    2. Python wrapper alternatives:
      1. cython
      2. HIP's python wrapper
      3. pybind11
      4. SWIG
    3. Java wrapper alternatives:
      1. Javacpp
  2. API design
    1. Determining if the CLIJ2 API is generic enough to be accessible from all platforms / if code can be copy-pasted between languages.
    2. Finding ways for language specific auto-generating APIs like in CLIJ2.
    3. Explore potential API-compatibility with scipy / cupy.
    4. Memory management (see forum)
  3. Wrapper development
    1. C++
    2. Python
    3. Java
    4. Macro
  4. User-documentation
    1. Introductory, partly generic, partly language specific
    2. Examples for all languages (Example generator?)
    3. Documentation generator as in CLIJ2.
    4. Four kinds of documentation
  5. Testing
    1. Automated tests for all platforms
    2. Integration tests, manual user-experience tests
    3. Cross-language testing

Target platforms

  1. Operating Systems
    1. Windows 10
    2. MacOS
    3. Ubuntu Linux
  2. Programming languages
    1. ImageJ Macro
    2. Fiji Jython
    3. Python
    4. Java
    5. Matlab
    6. Icy JavaScript
    7. C++
    8. Fiji Groovy
  3. Hardware (OpenCL version > 1.2)
    1. Intel HD GPUs
    2. NVidia GTX/RTX
    3. AMD GPUs (Vega)
    4. Apple Silicon M1


June 2020: Core development start

April 2021: Define new opencl-kernel format + documentation

July 2021: Reorganization of opencl-kernels

September 2021: Java/Python wrappers development start

September 2021: API mostly defined

December 2021: Core is functional, major wrapper code done.

February 2022: Alpha release of a minimal set of functions running on all target platforms and GPU hardware.

May 2022: Beta-release of full functionality

June 2022: Release of version 1.0. Code freeze to prevent breaking backwards compatibility

July 2022: Discussion of achievements and making a plan for version 2.0

Potential future extensions

CUDA support?

Compatiblilty with