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RAN-DBDEA-00007
Ranvier · DBDEA

Exam DBDEA Topics: platform Difficulty: hard

A machine learning team works interactively in notebooks, training models on GPU-enabled instances with Databricks Runtime for Machine Learning and several custom environment libraries. To reduce administration, they ask whether this workload can move to serverless compute. What should the data engineer answer?

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  1. A. Yes — serverless compute automatically attaches GPU instances when it detects ML libraries
  2. B. Yes — serverless compute supports every Databricks Runtime version, including ML runtimes
  3. C. No — interactive GPU training must be submitted as separate Lakeflow Jobs that each create a job cluster
  4. D. No — ML Runtime on GPU is not supported on serverless compute; use a classic compute resource
Reveal answer

Correct answer: No — ML Runtime on GPU is not supported on serverless compute; use a classic compute resource

Reference: https://docs.databricks.com/aws/en/compute/cluster-config-best-practices

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Official Answer (D): No — ML Runtime on GPU is not supported on serverless compute; use a classic compute resource

Ranvier · DBDEA

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