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This repo is an optimized CUDA version of FIt-SNE algorithm with associated python modules. We find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or up to 50x faster than Multicore-TSNE when used with the right GPU. You can install binaries with anaconda for CUDA version 10.1 and 10.2 using conda install tsnecuda -c conda-forge. Tsnecuda supports CUDA versions 9.0 and later through source installation, check out the wiki for up to date installation instructions....

The Open-Source PyMOL repository has been moved to github: https://github.com/schrodinger/pymol-open-source We still use the pymol-users mailing list here on sourceforge. Please subscribe for community support: https://pymol.org/maillist (Note: SourceForge email newsletter and special offers are optional and can be unchecked) The PyMOL community wiki has its own home: https://pymolwiki.org/

...Many practical aspects of the user interface are still in the planning and development phase. Those who wish to participate in the development of pyOSET are encouraged to subscribe to the Developer's Mailing List. End users who want up to date information on the status of releases should periodically check the project News link above, or subscribe to the RSS feed of that page.