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Scilab memory (stacksize) issues

Hi, I am a regular but intermediate to advanced user of Scilab. I find that I am unable to run large time-series simulations due to memory issues associated with stacksize. I find this too limiting. I have an 8GB RAM laptop, so I am not very short on memory resources. I would like to be able to create variable arrays that are at least 10M (M=million) in length, and quite a few ones like that. At present I keep getting the following stacksize exceeded message(s):

stack size exceeded!
Use stacksize function to increase it.
Memory used for variables: 9010013
Intermediate memory needed: 5
Total memory available: 10000000

I have tried to use stacksize() to set it to a higher limit, but it can only go up to 30000000, which is still very insufficient. Python seems to be able to handle much more. What can I do to stay with Scilab and get around these problems? I am using Scilab 5.5.2.

Any help and tips greatly appreciated.


Scilab 10-06-20, 12:29 p.m. vvadde@gmail.com
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03-12-21, 6:14 p.m. KlaraWAshburn

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09-01-22, 12:55 a.m. zxclord123

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If you allocate a large stack size, you will have to spread the space across many different stacks, which may result in a significant slowdown for your time-series simulations.
Scilab provides a few built-in functions to manage the stack size, wordle website but they are not very intuitive, so it’s often a good idea to write your own function to avoid potential stack overflow errors.
28-03-22, 3:33 p.m. tomcruise

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26-06-22, 4:13 a.m. Remedy51

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My experience with Scilab is limited, but my understanding is that the Stacksize option only affects how much data can be stored in memory at once. The actual amount of memory allocated to Scilab is not changed by this option. You should also visit https://grabmyessay.biz/ site as you can find professional essay writers here. My understanding is that a stack size of 1000 will allow you to store 1000 numbers on the stack before running out of memory; however, this does not mean that these 1000 numbers will take up 1000 bytes (as there are overhead costs for each number stored on the stack).
27-06-22, 5:07 p.m. Jacey55

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Scilab memory (stacksize) issues can occur when the memory allocated by the Scilab tool is not sufficient to run the system. Scilab allows users to allocate from a few hundred MB up to several GB of RAM. fnaf pokedle However, with larger systems, allocating more memory may be necessary, especially if using multiple processors simultaneously. 

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28-06-22, 7:58 a.m. otis123

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