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Could CI runtimes be reduced by heavily refactoring the 'test' Notebooks and fleshing out the unit test suite? Expanding the (currently trivial) unit test suite (Add unit tests #339) would bring the benefit of checks for correctness (NB at present the CI jobs only confirm that a number of Notebooks can be run, not that output cells are 'sufficiently correct').
Could switching to managing MuMoT as a conda package instead of a pip wheel bring about performance improvements through making it simpler to adopt an all-conda workflow inc. the Intel MKL for accelerating BLAS/LAPACK operations using multiple cores and SIMD?
Could certain parts of MuMoT benefit from profiling and optimisation? Vectorisation (numpy), JIT compilation (numba), AOT (cython) and/or multithreading/multiprocessing may be useful here.
The text was updated successfully, but these errors were encountered:
At present travis-ci.org jobs are taking ~50 mins and will likely be longer if/when PR #363 is merged:
The text was updated successfully, but these errors were encountered: