# Unable to allocate array with shape (74619, 8192) and data type float64

**URL:** https://forum.qiime2.org/t/unable-to-allocate-array-with-shape-74619-8192-and-data-type-float64/17094
**Category:** Technical Support
**Tags:** feature-classifier
**Created:** [October 15, 2020, 7:40am UTC](https://forum.qiime2.org/t/unable-to-allocate-array-with-shape-74619-8192-and-data-type-float64/17094 "2020-10-15T07:40:41Z")
**Posts on this page:** 1
**Showing post:** 6

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### Author: ![Nicholas\_Bokulich](https://forum.qiime2.org/user_avatar/forum.qiime2.org/nicholas_bokulich/32/19937_2.png) [@Nicholas\_Bokulich](https://forum.qiime2.org/u/Nicholas_Bokulich)
#### Post date: [October 20, 2020, 7:13pm UTC](https://forum.qiime2.org/t/unable-to-allocate-array-with-shape-74619-8192-and-data-type-float64/17094/6 "2020-10-20T19:13:39Z")

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> [@jose\_gacia](#):
>
> I was wondering If there´s a way of enhacing the performance/use of memory

Yes, please see the many existing topics on the forum that discuss troubleshooting memory errors. E.g., see this topic:

> [@Feature-classifiers error](https://forum.qiime2.org/t/feature-classifiers-error/11946/2):
>
> This is a memory error; essentially you do not have enough memory to open the SILVA classifier on your computer. This is low for the SILVA classifier — it will often take up to 32GB+ if left to its own devices! There's a couple of things you might be able to do. First, you can use the --p-reads-per-batch parameter (e.g., set to 1000 or 2000) to reduce the number of reads classified at a time. However, it looks like you do not have enough memory to load the SILVA classifier, not the reads, s…

Good luck!

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