Search Results for "numerical"

* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:...

MhcFS2 - engineering calculator. (v. 1.2 b141) (math expression calculator, scientific calculator, numerical, integral,integration, derivative, root, matrix, differencial, differentiation, equation, LSE,ODE )

...MFront is based on C++ and provides several domain specific languages which were designed to simplify the implementations of new material properties, mechanical behaviours and simple material models. A particular focus was made on mechanical behaviours which are by essence more complex and may have significant impact on the numerical performances of mechanical simulations. Various performance benchmarks show that the code generated using MFront is in most cases on par or better than other implementations, generally written in Fortran. For mechanical behaviours, MFront introduces interfaces for various finite element or FTT solvers (Cast3M, Code-Aster, ZeBuLoN, Abaqus, Europlexus, AMITEX_FFT, etc..). ...

GluCat is a generic library of C++ templates that implement universal Clifford algebras over the field of real numbers. The PyClical extension module for Python gives users an easy Python scripting interface for calculations in Clifford algebras. The name PyClical is an homage to Pertti Lounesto's CLICAL.

This project deals with a new concept of the heterogeneous grid for acceleration of the numerical linear algebra computing. We design this grid with respect to maximal ratio between cost and computational power. It allows a parallelization of scientific codes with minimal programming effort. We also optimize grid concept to be less sensitive to network parameters.

...The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy.