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HPE2-N69 Sample Questions Answers

Questions 4

An HPE Machine Learning Development Environment resource pool uses priority scheduling with preemption disabled. Currently Experiment 1 Trial I is using 32 of the pool's 40 total slots; it has priority 42. Users then run two more experiments:

• Experiment 2:1 trial (Trial 2) that needs 24 slots; priority 50

• Experiment 3; l trial (Trial 3) that needs 24 slots; priority I

What happens?

Options:

A.

Trial I is allowed to finish. Then Trial 3 is scheduled.

B.

Trial 2 is scheduled on 8 of the slots. Then, alter Trial 1 has finished, it receives 16 more slots.

C.

Trial 1 is allowed to finish. Then Trial 2 is scheduled.

D.

Trial 3 is scheduled on 8 of the slots. Then, after Trial 1 has finished, it receives 16 more slots.

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Questions 5

An ml engineer wants to train a model on HPE Machine Learning Development Environment without implementing hyper parameter optimization (HPO). What experiment config fields configure this behavior?

Options:

A.

profiling: enabled: false

B.

hyperparameters; optimizer:none

C.

searcher: name: single

D.

resources: slots_per_trial: 1

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Questions 6

A customer is deploying HPE Machine learning Development Environment on on-prem infrastructure. The customer wants to run some experiments on servers with 8 NVIDIA A too GPUs and other experiments on servers with only Z NVIDIA T4 GPUs. What should you recommend?

Options:

A.

Letting the conductor automatically determine which servers to use for each experiment, based on the number of resource slots required

B.

Deploying two HPE Machine Learning Development Environment clusters, one tor each server type

C.

Deploying servers with 8 GPUs as agents and using the conductor to run experiments that require only 2 GPUs

D.

Establishing multiple compute resource pools on the cluster, one tor servers or each type

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Questions 7

The ML engineer wants to run an Adaptive ASHA experiment with hundreds of trials. The engineer knows that several other experiments will be running on the same resource pool, and wants to avoid taking up too large a share of resources. What can the engineer do in the experiment config file to help support this goal?

Options:

A.

Under "searcher," set "max_concurrent_trails" to cap the number of trials run at once by this experiment.

B.

Under "searcher," set "divisor- to 2 to reduce the share of the resource slots that the experiment receives.

C.

Set the "scheduling_unit" to cap the number of resource slots used at once by this experiment.

D.

Under "resources.- set 'priority to I to reduce the share of the resource slots mat the experiment receives.

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Questions 8

At what FQDN (or IP address) do users access the WebUI Tor an HPE Machine Learning Development cluster?

Options:

A.

Any of the agent's in a compute pool

B.

A virtual one assigned to the cluster

C.

The conductor's

D.

Any of the agent's in an aux pool

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Questions 9

What is a benefit or HPE Machine Learning Development Environment, beyond open source Determined AI?

Options:

A.

Experiment tracking

B.

Model Inferencing

C.

Distributed training

D.

Premium dedicated support

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Questions 10

You are proposing an HPE Machine Learning Development Environment solution for a customer. On what do you base the license count?

Options:

A.

The number of servers in the cluster

B.

The number of agent GPUs

C.

The number of processor cores on agents

D.

The number of processor cores on all servers in the cluster

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Questions 11

What role do HPE ProLiant DL325 servers play in HPE Machine Learning Development System?

Options:

A.

They run validation and checkpoint workloads.

B.

They run training workloads that do not require GPUs.

C.

They host management software such as the conductor and HPCM.

D.

They run non-distributed training workloads.

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Questions 12

What is a benefit of HPE Machine Learning Development Environment mat tends to resonate with executives?

Options:

A.

It uses a centralized training architecture that is highly efficient.

B.

It helps DL projects complete faster for a faster ROI.

C.

It helps companies deploy models and generate revenue.

D.

It automatically cleans up data to create better end results.

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Exam Code: HPE2-N69
Exam Name: Using HPE AI and Machine Learning
Last Update: Jul 14, 2024
Questions: 40
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