clEsperanto: A GPU-accelerated image processing framework across languages and platforms

<p>Poster presented as part of the Crick BioImage Analysis Symposium.  </p> <p>clEsperanto is a collaborative open-source project, built on the evolution of the CLIJ platform, that aims to facilitate end-user access to modern computing hardware through an abstraction layer. Relying on a C++ low-level back-end structure, this layer allows calling GPU-accelerated image processing operations without the need for learning any specific complex language. Through this new architecture, the library is available for all major Bio-Image analysis softwares and languages while sharing the same functionnality and syntax, and running the same implementation.</p> <p><strong>References</strong></p> <p>Robert Haase, Loic A. Royer, et. al.  CLIJ: GPU-accelerated image processing for everyone, Nature Methods, 2020</p> <p>Robert Haase, Akanksha Jain, Stéphane Rigaud, et. al.  Interactive design of GPU-accelerated Image Data Flow Graph and cross-platform deployment using multi-lingual code generation, BiorXiv, 2020</p> <p>Robert Haase, Talley Lambert, Justin Kiggins, Johannes Müller, & Kevin Yamauchi. (2022). clEsperanto/napari_pyclesperanto_assistant: 0.21.0. Zenodo.</p> <p><em>Permission has been given by authors to upload to Crick Figshare. Copyright remains with the original holders.</em></p>