- sagemaker-training-toolkit VS image-super-resolution
- sagemaker-training-toolkit VS jina
- sagemaker-training-toolkit VS Activeloop Hub
- sagemaker-training-toolkit VS torchlambda
- sagemaker-training-toolkit VS spotty
- sagemaker-training-toolkit VS sagemaker-tensorflow-training-toolkit
- sagemaker-training-toolkit VS data-science-ipython-notebooks
- sagemaker-training-toolkit VS sagemaker-distribution
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sagemaker-training-toolkit reviews and mentions
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Distributed training with Horovod/MPI
I'm using sagemaker-training-toolkit to attempt hyperparameter optimization and trying to take advantage of all the cores on each machine using their MPI options (which uses Horovod with MPI to my understanding). I'm pretty new to this space and can't find anything that describes in somewhat lay-terms how training works in this distributed model. With AllReduce, how often does the reduce happen? I'm trying to figure out if all training threads are training a shared model such that every thread is training on the "latest" version of the model.
Stats
aws/sagemaker-training-toolkit is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of sagemaker-training-toolkit is Python.
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