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Help Center/ ModelArts/ FAQs/ Notebook (New Version)/ Others/ Why Is the Training Speed Similar When Different Notebook Flavors Are Used?

Why Is the Training Speed Similar When Different Notebook Flavors Are Used?

Updated on 2024-06-11 GMT+08:00

If your training job is single-process in code, the training speed is basically the same no matter when the notebook flavor of 8 vCPUs and 64 GB of memory or the flavor of 72 vCPUs and 512 GB of memory is used. For example, if your training job uses 2 vCPUs and 4 GB of memory, the training speed is similar no matter when you use the notebook flavor of 4 vCPUs and 8 GB of memory or the flavor of 8 vCPUs and 64 GB of memory.

If your training job is multi-process in code, the training speed backed by the notebook flavor of 72 vCPUs and 512 GB of memory is higher than that backed by the notebook flavor of 8 vCPUs and 64 GB of memory.

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