Intrepydd is a novel ahead-of-time (AOT) programming system for Python programmers who want faster code on current hardware, and also on future reconfigurable and heterogeneous systems being designed to address the challenges of post-Moore's-Law computing. The target audience for Intrepydd is Python programmers who are interested in writing data analytics kernels with the productivity of high-level Python code and the performance of low-level C/C++ code. This web site summarizes an early release (v0.2) of Intrepydd, finalized in May 2019, and will be updated as later releases become available.
Video Preview. For a quick screencast video overview, which goes through the k-means case study in the Jupyter-based tutorial, click here (YouTube).
Functions Reference. For a Jupyter-based summary and demo of many of the Intrepydd-supported functions, refer to the functions reference or its preview. Please also refer to the complete list of Intrepydd built-in functions and libraries list.
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