[Scilab-users] More rapid calculation

[fujimoto2005]

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 cumsum(wY1_M,'c') to linear algebra version
wY1_M*triu(ones(time_step,time_step)), calculation time increases to 2
minutes although CPU usage rate rose greatly. "cumsum" function seems
efficient function.

3, Is there any way to improve random number matrices generation? The
attached file is a snapshot of the task manager when generating random
matrices. It shows the CPU utilization remains low despite using many slots.
What is the cause?
snapshot_of_task_manager2.png
<http://mailinglists.scilab.org/file/t497065/snapshot_of_task_manager2.png>  

4, If I can generate multiple random matrices with smaller row size at the
same time and integrate them at the end, I expect the processing time will
be shorter, but can not  I do such a thing?

Best regards.



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