From: Albert S. <fu...@gm...> - 2006-10-28 00:59:43
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Hello all I managed to get NumPy to compile with the free for non-commercial use Linux versions of the Intel C compiler, version 9.1 and Intel MKL 8.1. Instructions at the bottom of this page: http://www.scipy.org/Installing_SciPy/Linux I ran the NumPy test suite, and it turned up a few test failures in test_ufunclike -- it seems the Intel C/MKL combo comes up with different answers for the sign of NaN. Compiling with -Wall turned up a few warnings, but nothing too serious. I submitted a ticket for the ones that seem easily fixable and might warrant a quick look: http://projects.scipy.org/scipy/numpy/ticket/366 I recently started building some of my other C code on Windows with the Intel compiler, and the speed increases in my application are quite dramatic. The Intel code is about 4 times faster than the code produced by Visual Studio .NET 2003. I suspect the speed increase is due to some loop vectorization. When compiling NumPy on Linux, some interesting messages pop up: numpy/core/src/arraytypes.inc.src(658) : (col. 9) remark: LOOP WAS VECTORIZED. numpy.distutils doesn't seem to support the Intel compiler on Windows, but if you have other C code lying around, you can easily use SCons to compile it with the Intel compiler (Intel offers 30-day evaluation versions of most of their products). Have fun! Cheers, Albert |