Enthought, Inc. Releases EPD 6.1: SciPy and NumPy Linked Against Intel MKL for Fast Linear Algebra

AUSTIN, Texas, March 3 /PRNewswire/ -- The Enthought Python Distribution bundles the Python programming language with over 75 additional libraries to support sophisticated analysis and visualization in scientific, financial, and engineering applications. EPD 6.1, released on March 2, 2010, includes MKL (Intel® Math Kernel Library) on Windows, OSX and Linux.*

MKL is an extensively threaded, highly optimized library. Its core math functions include BLAS, LAPACK, ScaLAPACK, Sparse Solvers, Fast Fourier Transforms, and Vector Math. These routines offer dramatic performance optimizations for applications that run on dual and multi-core Intel® processors.

In EPD 6.1, the linear algebra routines of NumPy and SciPy are linked dynamically against the MKL.  Previously, these linear algebra routines were linked against the ATLAS library on Windows and Linux, and to the Accelerate framework on OSX.  This allows EPD users to seamlessly benefit from the highly optimized BLAS and LAPACK routines in the MKL.  In addition, EPD 6.1 comes bundled with all of the MKL run-time libraries so that advanced users can take advantage (with ctypes) of even more of the MKL library such as Fast Fourier transforms, trust-region optimization methods, sparse solvers, and vector math.  

One-click installers grant immediate access to 32-bit and 64-bit versions of EPD for Windows, Linux, OSX, and Solaris.  Licenses are available to commercial users at four subscription levels, while academics may use 32-bit EPD free of cost.

*MKL is not available for Solaris and is consequently not included in EPD on that platform.

SOURCE Enthought, Inc.