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Forum Posts

DataBRObin
by New Contributor III
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Running Keras model training with HorovodRunner works until the training function is exited ("The MPI_Query_thread() function was called after MPI_FINALIZE was invoked.")

I am running training of a Keras/Tensorflow deep learning model on a cluster of (for now) 2 workers and 1 driver (T4 GPU, 28GB, 4 core) using the Databricks provided HorovodRunner. It all seems to go well and the performance scales quite nicely over ...

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sean_owen
Honored Contributor II
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I personally suspect it's your callbacks. Can you remove all those state callbacks and see if that is it?

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ppang
by New Contributor III
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Does Databricks Container Services (DCS) support for GPU containers with Databricks Runtime 11.3 LTS and higher?

I have been trying to start a cluster using DCS with GPU containers (https://github.com/databricks/containers/tree/master/ubuntu/gpu), but was only successful with Databricks Runtime 10.4 LTS and lower. With Databricks Runtime 11.3 LTS and higher, I ...

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alisher_pwc
by New Contributor II
  • 1702 Views
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Model serving with GPU cluster

Hello Databricks community!We are facing a strong need of serving some of public and our private models on GPU clusters and we have several requirements:1) We'd like to be able to start/stop the endpoints (best with scheduling) to avoid excess consum...

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Vartika
Moderator
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Hi @Alisher Akh​ Does @Debayan Mukherjee​'s answer help? If yes, would you be happy to mark the answer as best so that other members can find the solution more quickly? If not, please tell us so we can help you further. Cheers!

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sanjay
by Valued Contributor II
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Resolved! torch.cuda.OutOfMemoryError: CUDA out of memory

Hi,I am using pynote/whisper large model and trying to process data using spark UDF and getting following error.torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 172.00 MiB (GPU 0; 14.76 GiB total capacity; 6.07 GiB already allocated...

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Anonymous
Not applicable
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@Sanjay Jain​ : The error message suggests that there is not enough available memory on the GPU to allocate for the PyTorch model. This error can occur if the model is too large to fit into the available memory on the GPU, or if the GPU memory is bei...

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zzy
by New Contributor III
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Why is GPU accelerated node much slower than CPU node for training a random forest model on databricks?

I have a dataset about 5 million rows with 14 features and a binary target. I decided to train a pyspark random forest classifier on Databricks. The CPU cluster I created contains 2 c4.8xlarge workers (60GB, 36core) and 1 r4.xlarge (31GB, 4core) driv...

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Hubert-Dudek
Esteemed Contributor III
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In many cases, you need to adjust your code to utilize GPU.

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