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NEW QUESTION # 43
You are meeting with a customer how has several DL models deployed. Out wants to expand the projects.
The ML/DL team is growing from 5 members to 7 members. To support the growing team, the customer has assigned 2 dedicated IT start. The customer is trying to put together an on-prem GPU cluster with at least 14 CPUs.
What should you determine about this customer?
- A. The customer is a key target for HPE Machine Learning Development Environment, but not HPE Machine Learning Development System.
- B. The customer is not ready for an HPE Machine Learning Development solution, but you could recommend open-source Determined Al.
- C. The customer is not ready for an HPE Machine Learning Development solution. Out you could recommend an educational HPE Pointnext ASPS workshop.
- D. The customer is a key target for an HPE Machine Learning Development solution, and you should continue the discussion.
Answer: D
Explanation:
The customer is a key target for an HPE Machine Learning Development solution, and you should continue the discussion. With the customer's dedicated IT staff, the customer is ready to deploy an on-premise GPU cluster with at least 14 CPUs. The HPE Machine Learning Development Environment is a comprehensive solution that provides the tools and technologies required to develop, manage, and deploy ML models. It includes a distributed training framework, an orchestration layer, a powerful development environment, and an integrated MLOps platform. With this solution, the customer can expand their ML/DL projects and scale up their team.
NEW QUESTION # 44
A trial is running on a GPU slot within a resource pool on HPE Machine Learning Development Environment. That GPU fails. What happens next?
- A. The concluded reschedules the trial on another available GPU in the pool, and the trial restarts from the state of the latest training workload.
- B. The trial fails, and the ML engineer must manually restart it from the latest checkpoint using the WebUI.
- C. The conductor reschedules the trial on another available GPU in the pool, and the trial restarts from the latest checkpoint.
- D. The trial tails, and the ML engineer must restart it manually by re-running the experiment.
Answer: C
Explanation:
If a GPU fails during a trial running on a resource pool on HPE Machine Learning Development Environment, the conductor will reschedule the trial on another available GPU in the pool, and the trial will restart from the latest checkpoint. The trial will not fail, and the ML engineer will not have to manually restart it from the latest checkpoint using the WebUI.
NEW QUESTION # 45
What is one key target vertical (or HPE Machine Learning Development solutions?
- A. Retail
- B. Hospitality
- C. Manufacturing
- D. K-12education
Answer: C
NEW QUESTION # 46
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