What is the difference between data parallelism and model parallelism?
An example of an AI chatbot conversation about data parallelism vs model parallelism.
What is the difference between data parallelism and model parallelism?
Data parallelism involves splitting data across multiple processors, while model parallelism splits the model itself.
Can you give me an example of when to use each type?
Sure! Use data parallelism for large datasets and model parallelism for complex models that don't fit in memory.
What are the advantages of each approach?
Data parallelism is easier to implement and scales well, while model parallelism allows for handling larger models.
Are there any downsides to these methods?
Yes, data parallelism can lead to communication overhead, and model parallelism can be complex to manage.
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