Effacer les filtres
Effacer les filtres

large matrix and memory space

8 vues (au cours des 30 derniers jours)
Massimo Laspia
Massimo Laspia le 20 Juin 2017
Goodmornig, I need to work with large matrix for simulation purposes. How can I manage these matrix without incurring in out of memory error? Is there a way to store matrix and save space?
Thanks
Regards
  2 commentaires
KSSV
KSSV le 20 Juin 2017
What's the dimension of matrix you work with? What problem? All ways there is chance of running our code on chunk of a matrix to avoid memory problems.
Adam
Adam le 20 Juin 2017
doc matfile
can help, by keeping the data on disk rather than in memory, but it does have restrictions on how you can access the data and is obviously slower (though less so that reading from disk manually every time)

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Réponses (2)

Jan
Jan le 20 Juin 2017
It depeneds on what "large" is. If you have some GigaBytes, install more RAM. Having the double size of the array as free RAM is a point to start from, but it is a good idea to install even more RAM. Then increase the virtual memory.
If you have an array with TerraBytes of data, this option has its limits. Then process the array in chunks. In both cases there is no magic switch to save space - except the array contains a lot of zeros: Then a sparse array will help you.
  1 commentaire
Massimo Laspia
Massimo Laspia le 20 Juin 2017
thanks

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Steven Lord
Steven Lord le 20 Juin 2017
As Jan said, it depends on what "large" means. Sparse matrices are one option if your data is sparsely populated. If your matrices are REALLY large, consider some of the tools designed for working with Big Data.

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