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Matlab 2010b 16

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The huge difference is because in MATLAB you are only calculating the eigenvalues but in python/numpy you are calculating both eigenvalues and eigenvectors. To correct this and make appropriate comparisons, you must do one of the following:1. change numpy.linalg.eig(x) to numpy.linalg.eigvals(x) , leave matlab code as it is OR2. change eig(x) to [V,D] = eig(x) in matlab, leave python/numpy code as it is (this might create more memory being consumed by matlab script) in my experience, python/numpy optimized with MKL(the one provided by Christoph Gohlke) is as fast as or slightly faster than matlab(2011b)optimized with MKL.

Hello linuS, I do not think your opinion is right, becaus: in Matlab 2010b, I used [V, D] = eig(X) as your suggestion (2.) to calculate both eigen vectors and eigen values. I do not find any useful purpose if we only calculate eigen values. You can see some other results at my blog: -3-2-vs-matlab-and-openblaslapack-on-matrix-multiply-svd-and-eig-tests/

I am sorry linuS, but I did not clearly understand your comment. I just care about 32 bit float matrix and I want to find the fastest tool to calculate eigen vectors and eigen values of a rectangular matrix. But I also tested with 64 bit float maxtrix and on my machine, Matlab 2010b is still faster than Python 3.2 with Numpy-MKL 1.6.2.

These commands are typed in a DOS window, in the $MATLAB\etc\win32win64 directory (where $MATLAB is the root MATLAB directory)($MATLAB\flexlm for releases prior to R2010b on Windows). There is also a graphical user interface (GUI) for these commands on Windows called LMTOOLS (see next section)

FLEXnet provides a graphical user interface (GUI) to its license management tools for Windows. For MATLAB installations, you can invoke this GUI by double-clicking on the lmtools.exe file in the $MATLAB\etc\win32win64 directory (where $MATLAB is the root MATLAB directory)($MATLAB\flexlm for releases prior to R2010b on Windows). The GUI uses buttons to provide access to the same set of tools as the lmutil script (also located in same directory) and displays the results returned in an integrated display window.

or use the lmtools GUI, lmtools.exe, found in in the $MATLAB\etc\win32win64 directory($MATLAB\flexlm for releases prior to R2010b on Windows), to check the status of licenses. This feature became available as of MATLAB 6 (R12). This output will show who has each license checked out, where they checked it out, and when they checked it out.

The license log files can be used to diagnose configuration problems or daemon software errors. Under Windows, the log file is called lmlog.txt, and can be found in $MATLAB\etc\win32win64 (where $MATLAB is the root MATLAB directory)($MATLAB\flexlm for releases prior to R2010b on Windows) on the license server. Under UNIX, Linux, and Mac the log file is called lm_TMW.log, and can be found in /var/tmp on the license server.

#!/bin/bash#SBATCH --job-name="rfm_RunMATLABTest_job"#SBATCH --ntasks=1#SBATCH --ntasks-per-node=1#SBATCH --output=rfm_RunMATLABTest_job.out#SBATCH --error=rfm_RunMATLABTest_job.err#SBATCH --time=0:10:0#SBATCH -p small,large,ram256g,ram1tmodule load matlab/R2019awget matlab -nodisplay -nodesktop -nosplash -r "run('script.m'); exit;"

A 3D isosurface MATLAB plot revealing the geodesic dome structure of a carbon-60 fullerene molecule. Image courtesy of the MathWorks. MathWorks has announced Release 2010b of its MATLAB and Simulink product families. The expanded set of tools and features in this release include new communications system design capabilities in MATLAB, automated PID controls tuning, GigE Vision hardware standard support, and enhanced Simulink and Stateflow support for creating reusable models.

With R2010b, Simulink offers a new signal type and subsystem enhancements that the company says help reduce block counts, simulation time, and memory usage for large models. New capabilities for capturing design variants and configurations in Simulink and creating reusabl


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