Scaling up the benchmark infrastructure of scikit-learn – Scikit-Learn Consortium

The Scikit-Learn Consortium at Inria foundation proposes an internship for scaling up the benchmark infrastructure of scikit-learn. The goals of the internship are:

Development of an automated benchmark suite to monitor Scikit-learn’s efficiency against third party libraries like daal4py, cuML and ONNX.
Analysis of the results: identify which scikit-learn models are the most under-performing and try to understandthe root cause by reading the source code and analyzing the space and time complexity of the algorithmsimplemented in each framework.
Follow up by profiling for more fine-grained analysis on the critical parts of these models.
Work on a pull request to improve the efficiency or multi-core scalability of one of those under-performingmodels.

The internship will take place at Inria Saclay (Campus Ecole Polytechnique, Bat. Turing, 91120 Palaiseau,France) or remotely depending on the evolution of the Covid situation.

The Scikit-Learn Consortium team is embedded in the Inria Parietal research team. Therefore the candidate will get an experience of working in an academic environment leading research of state-of-art mathematical tools for machine learning applied to neuroscience problems.

The duration of the internship will be of 5 to 6 months.

Click here to download the detailed description.