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HP Using HPE Cray AI Development Environment Sample Questions (Q30-Q35):
NEW QUESTION # 30
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?
- 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.
Answer: D
Explanation:
Trial 3 is scheduled on 8 of the slots. Then, after Trial 1 has finished, it receives 16 more slots. This is because priority scheduling is used in the HPE Machine Learning Development Environment resource pool, which means higher priority tasks will be given priority over lower priority tasks. As such, Trial 3 with priority 1 will be given priority over Trial 2 with priority 50.
NEW QUESTION # 31
ML engineers are defining a convolutional neural network (CNN) model bur they are not sure how many filters to use in each convolutional layer. What can help them address this concern?
- A. Distributing the training across multiple CPUs
- B. Using a variable learning late
- C. Using hyperparameter optimization (HPO)
- D. Training the model on multiple epochs
Answer: C
Explanation:
Hyperparameter optimization is a process of tuning the hyperparameters of a machine learning model, such as the number of filters in a convolutional neural network (CNN) model, to determine the best combination of hyperparameters that will result in the best model performance. HPO techniques are used to automatically find the optimal hyperparameter values, which can greatly increase the accuracy and performance of the model.
NEW QUESTION # 32
At what FQDN (or IP address) do users access the WebUI Tor an HPE Machine Learning Development cluster?
- A. A virtual one assigned to the cluster
- B. The conductor's
- C. Any of the agent's in a compute pool
- D. Any of the agent's in an aux pool
Answer: B
Explanation:
The WebUI for an HPE Machine Learning Development cluster can be accessed at the FQDN or IP address of the conductor. The conductor is responsible for managing the cluster and providing access to the WebUI.
NEW QUESTION # 33
You are helping a customer start to implement hyper parameter optimization (HPO) with HPE Machine learning Development Environment. An ML engineer is putting together an experiment config file with the desired Adaptive A5HA settings. The engineer asks you questions, such as how many trials will be trained on the max length and what the min length for all trials will be.
What should you explain?
- A. The engineer should upload the experiment config to the HPE Machine Learning Development Environment WebUl and view the graph of the experiment plan.
- B. The engineer should run the "det preview-search" command, referencing the experiment config.
- C. The engineer should access the HPE Machine Learning Development online calculator and input the mode, max_trials, max_length, divisor, and max_runs.
- D. The engineer should run a preliminary experiment with one tenth the desired number of max trials, assess the results, and then run the full experiment.
Answer: D
NEW QUESTION # 34
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?
- A. Letting the conductor automatically determine which servers to use for each experiment, based on the number of resource slots required
- B. Deploying servers with 8 GPUs as agents and using the conductor to run experiments that require only 2 GPUs
- C. Establishing multiple compute resource pools on the cluster, one tor servers or each type
- D. Deploying two HPE Machine Learning Development Environment clusters, one tor each server type
Answer: C
NEW QUESTION # 35
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