DADiSP / MatrixXL
Matrix acceleration module
A matrix is a rectangular array of values that lies at the heart of a wide variety of technical applications, including signal processing, medical, geophysical, acoustic, statistics, image processing and many more. Matrices are used to find solutions to systems of equations, perform numeric optimisations and compute linear transformations. Matrix decompositions provide simplified factorisations of matrices to implement efficient matrix computations for a large class of matrix problems.
LAPACK (Linear Algebra PACKage) is a software library for numerical linear algebra and provides industry standard routines for solving systems of linear equations and linear least squares, eigenvalue problems and singular value decomposition. LAPACK also includes routines to implement matrix factorisations such as LU, QR, Cholesky and Schur decomposition.
Processor tuned performance
The MatrixXL module is based on the LAPACK implementation from Intel’s MKL library to provide outstanding performance on Intel based processors. MatrixXL automatically takes advantage of the latest instruction sets, parallelism and algorithms to yield a highly optimised matrix functionality. Performance gains of 3x to 50x over the standard built-in matrix functions are acheived.
MatrixXL is completely automatic, simply install the module and matrix functions immediately run faster: no settings to change, no code to rewrite. In addition to core matrix routines any custom or built-in function that relies on matrix processing experiences the same performance gain. MatrixXL is a straightforward way to accelerate any matrix based data analysis.
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Huge amount learnt, much more than I expected. Appreciate the ability of the programme much more than I did before.PA, Liverpool, UK
Good balance of basic information and practical tips for the more experiencedDV, Manchester, UK
Bob worked tirelessly over many hours (and days!) to try to resolve the issue. His efforts were truly appreciated on my behalf. He was polite, caring and nothing was too much trouble. Many, many thanks Bob.JO
Ref: Mathtype 6.6a. I love this product, thanks for decent support on this softwareJT, Derbyshire, UK
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