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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 optimizations and compute linear transformations. Matrix decompositions provide simplified factorizations of matrices to implement efficient matrix computations for a large class of matrix problems.

LAPACK 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 factorizations such as LU, QR, Cholesky and Schur decomposition.

MatrixXL Perfomance Gains

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 optimized 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 and is the perfect complement to DADiSP/FFTXL, the FFT Acceleration Module and DADiSP/VectorXL, the Vector Math Acceleration Module. Or for the most cost effective solution to speeding up nearly any numeric calculation, see the DADiSP/ProPac module that combines all three accelerators into a single, highly optimized numeric computation engine to provide some of the most efficient technical data analysis routines available today.


DADiSP/MatrixXL requires DADiSP 6.5 B04 or higher. Contact us for information about updating your current version of DADiSP.

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