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.

Matrix barLAPACK library

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.

Simple deployment

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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