I am using KNIME for chemical analytical modelling. I have used KNIME on a standard local computer with 8 RAM. I want to do a scale-up of my models and need a lot more computing power now (which I have not been able to predict yet, because the modelling process isn’t finnished). My old models used 600 MB RAM, which might exponetially increase with my new approaches to.
I want to buy new hardware to work on to reduce the calculation time, but I am unsure about the setup. I want to keep it local and don’t want to run the modelling process on external servers.
Now I would like to know if KNIME is able to work on graphic cards or if I should work with multiple CPU’s. Any experience of your own setup would be very helpful.
Thanks in advance!
welcome to the KNIME Forum! What kind of models are you running? Are you using KNIME native learner nodes or are you training the models in a Python or R learner?
Thanks for your reply.
I have only used KNIME native learner nodes and R learner nodes (like R predictor and R Learner) until now. I have not been planning on training models in a Python learner yet.
Do the native learner nodes and R learner nodes benefit from graphic cards or are they only working on CPUs?
the native KNIME Learner nodes do not make use of a graphics card. In that case I suggest a fast CPU and as much memory as you can afford
Okay thanks so much! Then I will focus on CPUs and Memory.
One last question: Which nodes benefit from graphic cards? Just so I know for future modelling and workflows.
as far as I know only the Deep Learning nodes benefit from a good graphics card.
Anything deeplearning related, eg. the keras/tensorflow nodes if setup correctly or thew deeplearning4j nodes.
On that regards what doesn’t work but would be a nice feature is that the xgboost nodes could also use GPU if one is available.
Hint: If you buy a GPU, buy one from Nvida and not AMD. Else you will enter a world of hurt if your interest is deep learning.
Bascially if you are doing deep learning, you will need an Nvida GPU, if not, then focus on CPU cores and speed (soem stuff is onyl single-threaded by nature). Also for knime IO matters so having the workspace on an ssd will also help.
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