lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-11-10 10:21:59 +00:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

Add section about GPU support

Browse Source 
#5158 #5085 #3704 #2754
This commit is contained in:
Matthias 2021-06-20 10:36:18 +02:00
parent 7f434c0413
commit 97351c95c0
1 changed files with 16 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
docs/faq.md
View File

@ -136,6 +136,22 @@ On Windows, the `--logfile` option is also supported by Freqtrade and you can us
> type \path\to\mylogfile.log | findstr "something"
```
### Why does freqtrade not have GPU support?
First of all, most indicator libraries don't have GPU support - as such, there would be little benefit for indicator calculations.
The GPU improvements would only apply to pandas-native calculations - or ones written by yourself.
For hyperopt, freqtrade is using scikit-optimize, which is built on top of scikit-learn.
Their statement about GPU support is [pretty clear](https://scikit-learn.org/stable/faq.html#will-you-add-gpu-support).
GPU's also are only good at crunching numbers (floating point operations).
For hyperopt, we need both number-crunching (find next parameters) and running python code (running backtesting).
As such, GPU's are not too well suited for most parts of hyperopt.
The benefit of using GPU would therefore be pretty slim - and will not justify the complexity introduced by trying to add GPU support.
There is however nothing preventing you from using GPU-enabled indicators within your strategy if you think you must have this - you will however probably be disappointed by the slim gain that will give you (compared to the complexity).
## Hyperopt module
### How many epochs do I need to get a good Hyperopt result?