Re: [Scilab-users] More rapid calculation

Dear Mottelet Thank you for your useful advice. 1, By changing repmat(timePoints_V,2*sample,1) to timePoints_M=ones(2*sample,1)*timePoints_V and using it, calculation time is improved by 25 seconds. 2, "cumsum" is not a bottleneck because it takes only 2 seconds to finish. Also, if I change

Re: [Scilab-users] More rapid calculation

Here is an example where 100% CPU is used (4 cores) with pure linear algebra. S. Quoting stephane.motte...@utc.fr: If your program does not take advantage of the MKL Intel library, it means that its CPU usage is not dominated by linear algebra stuff. If you don't tell us more we won't be

Re: [Scilab-users] More rapid calculation

Le 15/02/2018 à 00:02, fujimoto2005 a écrit : Sorry, my code contains line "exec user file " I attached revised version which contains the line as a user function. Please see it. Best regards corSmplebaseZ1andZ2_with_UserFunc.sce

Re: [Scilab-users] More rapid calculation

Sorry, my code contains line "exec user file " I attached revised version which contains the line as a user function. Please see it. Best regards corSmplebaseZ1andZ2_with_UserFunc.sce -- Sent from:

Re: [Scilab-users] More rapid calculation

Dear all Thank you for your replies. I attached my code and a snapshot of task manager. The snapshot shows a typical situation. CPU utilization is usually between 10 and 20%. There are about 3 times when the CPU utilization instantaneously reaches from 40% to 50%. The memory usage does not exceed

Re: [Scilab-users] More rapid calculation

Here is an example (pure linear algebra) using 100% cpu (4 cores) : http://www.utc.fr/~mottelet/Images/cpu.png S. Quoting stephane.motte...@utc.fr: If your program does not take advantage of the MKL Intel library, it means that its CPU usage is not dominated by linear algebra stuff. If

Re: [Scilab-users] More rapid calculation

Le 14/02/2018 à 19:15, stephane.motte...@utc.fr a écrit : If your program does not take advantage of the MKL Intel library, it means that its CPU usage is not dominated by linear algebra stuff. I was actually wondering that the bootle neck is not the CPU. This is why i was thinking about

Re: [Scilab-users] More rapid calculation

If your program does not take advantage of the MKL Intel library, it means that its CPU usage is not dominated by linear algebra stuff. If you don't tell us more we won't be able to help... S. Quoting fujimoto2005 : Dear Mottellet But there is an explanation "If

Re: [Scilab-users] More rapid calculation

Dear Mottellet But there is an explanation "If we use the Intel MKL on Windows, then Scilab use all the cores available on the processor. " https://wiki.scilab.org/Documentation/ParallelComputingInScilab So I expected there are some ways to increase the usage of cpu. -- Sent from:

Re: [Scilab-users] More rapid calculation

Hello, If your problem is embarrassingly parallel (ie you run your simulations many times independently for different random matrices), you might speed up the overall simulation by running more than one instance of scilab in parallel. Antoine Le 14/02/2018 à 18:00, Stéphane Mottelet a

Re: [Scilab-users] More rapid calculation

Hello, A priori, there is no reason why your calculation should use more than one CPU core, which explains why you see only 1/8=12,5% CPU use. S. Le 14/02/2018 à 14:35, fujimoto2005 a écrit : I am using 6.00 for windows. I am doing a simulation using a random number matrix with a huge

Re: [Scilab-users] More rapid calculation

Dear Samuel Thanks for your reply. My PC is equipped with 64GB SDRAM. Isn't it enough? Best regards. -- Sent from: http://mailinglists.scilab.org/Scilab-users-Mailing-Lists-Archives-f2602246.html ___ users mailing list users@lists.scilab.org

Re: [Scilab-users] More rapid calculation

Le 14/02/2018 à 14:35, fujimoto2005 a écrit : I am using 6.00 for windows. I am doing a simulation using a random number matrix with a huge size. The size of the random matrix is 10 ^ 4 x 25000. I am using a PC equipped with 8 cores and 16 threads. It takes a considerable time to finish the

[Scilab-users] More rapid calculation

I am using 6.00 for windows. I am doing a simulation using a random number matrix with a huge size. The size of the random matrix is 10 ^ 4 x 25000. I am using a PC equipped with 8 cores and 16 threads. It takes a considerable time to finish the simulation, but CPU utilization is as low as 10-20%.