On Wed, May 11, 2016 at 12:00 PM, beliavsky--- via Python-list <python-list@python.org> wrote: > The Intel Distribution for Python 2017 Beta > https://software.intel.com/en-us/python-distribution is available for > Windows, Linux, and Mac OS for Python 2.7 and 3.5. > > "The Beta product adds new Python packages like scikit-learn, mpi4py, numba, > conda, tbb (Python interfaces to Intel® Threading Building Blocks) and pyDAAL > (Python interfaces to Intel® Data Analytics Acceleration Library). The Beta > also delivers performance improvements for NumPy/SciPy through linking with > performance libraries like Intel® MKL, Intel® Message Passing Interface > (Intel® MPI), Intel® TBB and Intel® DAAL." > > I just installed Intel Python today. Has anyone tried it? Does it run your > programs faster than the usual CPython? >
I haven't used it, but based on a reading of their blurbs, I suspect you won't see any significant improvement in base Python code - the advantage is the numeric computation work. For general Python performance, check out PyPy, although it tends to lag behind CPython in versions somewhat. However, PyPy doesn't do anything for your numpy performance, and doesn't even guarantee that everything works: http://pypy.org/download.html#installing-numpy So if the Intel Math Kernel Library lives up to the descriptions, it might be the thing to fill in this gap - "use PyPy to speed up your Python code, or Intel Python to speed up your numpy code". (Most programs won't have performance issues on both of those at once.) It's worth noting that Intel engineers have been proposing a number of performance improvements for backporting into the CPython core, and some of them even made it into 2.7. I've no idea whether the page you linked to is part of the same project or not; it might be completely separate, or it might be the source of all those improvements. ChrisA -- https://mail.python.org/mailman/listinfo/python-list
