Suppose I have a 16 core machine, and an embarrassingly parallel program.I use lots of numpy dot products and addition of numpy arrays, and if I did not use multiprocessing it would be a no-brainer:Ma
I\'m looking for a good guide on how to incorporate BLAS or LAPACK functions into my Objective C Program developed through Xcode.The only sources I can find online of programs in BLAS/LAPACK are writt
Is there a means to do element-wise vector-vector multiplication with BLAS, GSL开发者_运维百科 or any other high performance library ?(Taking the title of the question literally...)
I would like to write a program that makes extensive use of BLAS and LAPACK linear algebra functionalities. Since performance is an issue I did some benchmarking and would like know, if the approach I
Lapack 开发者_如何学编程3.2.1 is not fully theard safe right...but 3.3 is which is recently being released by netlib with help of intel.
How do I apply level 1 blas on a boost::numeric::ublas matrix? For example I want t开发者_开发问答o compute the maximum entry or the sum of all entries.
I\'m attempting to do a release of some software开发者_C百科 and am currently working through a script for the build process. I\'m stuck on something I never thought I would be, statically linking LAP
I\'ve got an algorithm that does tree steps of linear algebra over and over again, loop{ first I multiply a Vector and a Matrix,
Why does BLAS have a 开发者_运维技巧gemm function for matrix-matrix multiplication and a separate gemv function for matrix-vector multiplication?Isn\'t matrix-vector multiplication just a special case
I just installed GSL and BLAS on Visual Studio 2010 successfully using this guide: However the matrix multiplications using cblas are ridicously slow. A friend on Linux had the same problem. Instead
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