What are the different types of parallelism in machine learning?
An example of an AI chatbot conversation about types of parallelism in machine learning.
What are the different types of parallelism in machine learning?
In machine learning, there are mainly three types of parallelism: data parallelism, model parallelism, and pipeline parallelism.
Can you explain data parallelism in more detail?
Sure! Data parallelism involves splitting the dataset into smaller chunks and processing them simultaneously across multiple processors.
What about model parallelism?
Model parallelism is when different parts of a model are distributed across multiple processors, allowing for larger models to be trained.
And what is pipeline parallelism?
Pipeline parallelism breaks the model into stages, where each stage processes data in a sequential manner, allowing for efficient training.
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