Matrices multiplication on Windows – Matlab is the champion again

Today, I test big matrices (float) multiplication on my laptop (HP Elitebook 6930p – Duo 2 Core 2×2.4Ghz, 4Gb Ram, Windows 7 32 bit, VS 2010) with OpenCV 2.3.1, Armadillo 3.0.2, Eigen 3.0.5 and OpenBLAS 1.0, C/C++ simple matrices multiplication method and Matlab 2010b 32bit. The program is simple: A = matrix(dim1, dim2, float), B = matrix(dim2, dim3, float), C = A*B, ofcourse I did not include the initial time, just the time for calculation. And here are the results.

Matrices’ size C Armadillo OpenCV Eigen C++ (use STL vector class) OpenBLAS Matlab
1000×1000 1.45 0.125 1.76 0.87 1.47 0.062 0.062
2000×2000 11.64 0.94 14.2 6.93 11.23 0.99 0.54
3000×3000 38.11 3.28 47.2 23.51 37.99 1.75 1.7
4000×4000 90.84 7.33 110.37 53.7 90.2 7.91 4.2
5000×5000 180.74 15.65 213.4 104.11 181.02 10.8 7.3
6000×6000 315.46 27.32 376.46 186.1 316.3 25.33 12.74

It is clear that Matlab is the champion, like in SVD test, but I do not understand why OpenCV is the slowest, even slower than simple C and C++ implementation (C and C++ implementation have the same speed). OpenCV is two times slower than Eigen, Armadillo (in my test – I use OpenBLAS with Armadillo) have the same speed with OpenBLAS. I also notice that simple C/C++, OpenCV, Eigen use only one Core and Armadillo, OpenBLAS and Matlab use both 2 Cores of my machine.

5 Responses to “Matrices multiplication on Windows – Matlab is the champion again”

  1. Mark Tall Says:

    Did you turn on optimisations in the compiler ? For template libraries this is critical.

    Also, why are you still using a 32 bit operating system on a 64 bit machine?

    • 4fire Says:

      I use VS 2010 and build with Release option. I do not known other optimize options for VS. I use 32 bit because my machine is 32 bit. I think the comparision is fair because all the libraries and Matlab is used default settings and on the same system (with the same matrices type). I known many people said that Windows is not reliable and slow, but that the reason we need better and faster programs. I supposed that Matlab is the fastest because it use Intel’s MKL library. I want to test ATLAS but I could not build it on my Windows system.

  2. rin Says:

    I guess you missed something about optimization as according to my experience there is no way to get 23.51 sec timing result for 3k x 3k matrix multiplication on eigen while matlab gives 1.7 sec because in some cases eigen gives better results than mkl. Could you share build configuration of eigen, opencv and armadillo.

    • 4fire Says:

      Sorry man. I used default setting for OpenCV 2.3.1 and Eigen 3.0.5 because I did not know how to configure them for better performance, could you show me how? I only set Armadillo to use BLAS and Lapack for the test.

  3. levan Says:

    ” I also notice that simple C/C++, OpenCV, Eigen use only one Core and Armadillo, OpenBLAS and Matlab use both 2 Cores of my machine.” so result are obvious: 2 cores are faster then one core alone 🙂 ….

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