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HP HPE2-N69 Exam Syllabus Topics:
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NEW QUESTION 18
You want to set up a simple demo Ouster tor HPE Machine learning Development Environment for the open source Determined AI) on a local machine. You plan to use "del deploy" to set up the cluster. What software must be installed on the machine before you run that command?
- A. Terralorm
- B. Kubernetes
- C. Docker
- D. PyTorch
Answer: B
NEW QUESTION 19
What is one of the responsibilities of the conductor of an HPE Machine Learning Development Environment cluster?
- A. It ensures experiment metadata is stored.
- B. It uploads model checkpoints.
- C. it downloads datasets for training.
- D. It validates trained models.
Answer: B
NEW QUESTION 20
An ML engineer is running experiments on HPE Machine Learning Development Environment. The engineer notices all of the checkpoints for a trial except one disappear after the trial ends. The engineer wants to Keep more of these checkpoints. What can you recommend?
- A. Adjusting how many of the latest and best checkpoints are saved in the experiment config's checkpoint storage settings.
- B. Double-checking that the checkpoint storage location is operating under 90% of total capacity.
- C. Adjusting the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage.
- D. Monitoring ongoing trials In the WebUl and clicking checkpoint nags to auto-save the desired checkpoints.
Answer: C
NEW QUESTION 21
You want to set up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined all on a local machine. Which OS Is supported?
- A. Red Hat 7-based Linux
- B. Windows Server 2016 or above
- C. HP-UX v11i
- D. Windows 10 or above
Answer: A
Explanation:
The OS supported for setting up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined on a local machine is Red Hat 7-based Linux. Red Hat 7-based Linux is an open source operating system that is used extensively in enterprise applications. It provides a stable and secure platform for running applications and is suitable for use in a demo cluster.
NEW QUESTION 22
Where does TensorFlow fit in the ML/DL Lifecycle?
- A. it provides pipelines to manage the complete lifecycle.
- B. it helps engineers use a language like Python to code and trail DL models.
- C. It adds system and GPU monitoring to the training process.
- D. It is primarily used to transport trained models to a deployment environment.
Answer: A
Explanation:
TensorFlow provides pipelines to manage the complete lifecycle of ML/DL models, from data ingestion to model training, evaluation, and deployment. It helps engineers use a language like Python to code and train DL models, and it also adds system and GPU monitoring to the training process. Additionally, it can be used to transport trained models to a deployment environment.
NEW QUESTION 23
Your cluster uses Amazon S3 to store checkpoints. You ran an experiment on an HPE Machine Learning Development Environment cluster, you want to find the location tor the best checkpoint created during the experiment. What can you do?
- A. Look for a "determined-checkpoint/" bucket within Amazon S3, referencing your experiment ID.
- B. In the experiment config that you used, look for the "bucket" field under "hyperparameters." This is the UUID for checkpoints.
- C. In the Web Ul, go to the Task page and click the checkpoint task that has the experiment ID.
- D. Use the "det experiment download -top-n I" command, referencing the experiment ID.
Answer: D
NEW QUESTION 24
An ML engineer is running experiments on HPE Machine Learning Development Environment. The engineer notices all of the checkpoints for a trial except one disappear after the trial ends. The engineer wants to Keep more of these checkpoints. What can you recommend?
- A. Adjusting the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage.
- B. Double-checking that the checkpoint storage location is operating under 90% of total capacity.
- C. Adjusting how many of the latest and best checkpoints are saved in the experiment config's checkpoint storage settings.
- D. Monitoring ongoing trials In the WebUl and clicking checkpoint nags to auto-save the desired checkpoints.
Answer: C
Explanation:
The best recommendation for an ML engineer running experiments on HPE Machine Learning Development Environment to keep more of the checkpoints is to adjust the experiment config's checkpoint storage settings to save more of the latest and best checkpoints. This can be done by monitoring ongoing trials in the WebUI and clicking checkpoint flags to auto-save the desired checkpoints. Additionally, the engineer should double-check that the checkpoint storage location is operating under 90% of total capacity to ensure that enough capacity is available to store the checkpoints. Finally, they can adjust the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage if desired.
NEW QUESTION 25
You are meeting with a customer, and MUDL engineers express frustration about losing work flue to hardware failures. What should you explain about how HPE Machine Learning Development Environment addresses this pain point?
- A. The solution can take periodic checkpoints during the training process and automatically restart failed training from the latest checkpoint.
- B. The solution automatically mirrors the training process on redundant agents, which take over If an issue occurs.
- C. The conductor and each of the agents ate deployed in an active-standby model, which protects in case of hardware issues.
- D. The solution continuously monitors agent hardware and sends out proactive alerts before failed hardware causes training to tail.
Answer: A
Explanation:
The best way to explain how HPE Machine Learning Development Environment addresses this pain point is to mention that the solution can take periodic checkpoints during the training process and automatically restart failed training from the latest checkpoint. This ensures that in case of a hardware failure, the engineers will not lose their work and training can be resumed from the last successful checkpoint.
NEW QUESTION 26
At what FQDN (or IP address) do users access the WebUI Tor an HPE Machine Learning Development cluster?
- A. Any of the agent's in an aux pool
- B. The conductor's
- C. A virtual one assigned to the cluster
- D. Any of the agent's in a compute 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 27
The 10 agents in "my-compute-poor nave 8 GPUs each, you want to change an experiment config to run on multiple GPUs at once. What Is a valid setting tor "resources_per_trial?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: D
NEW QUESTION 28
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. Any of the agent's in a compute pool
- C. The conductor's
- D. Any of the agent's in an aux pool
Answer: D
NEW QUESTION 29
What role do HPE ProLiant DL325 servers play in HPE Machine Learning Development System?
- A. They host management software such as the conductor and HPCM.
- B. They run validation and checkpoint workloads.
- C. They run non-distributed training workloads.
- D. They run training workloads that do not require GPUs.
Answer: A
NEW QUESTION 30
You want to set up a simple demo cluster for HPE Machine Learning Development Environment (or the open source Determined Al) on Amazon Web Services (AWS). You plan to use "det deploy" to set up the cluster. What is one prerequisite?
- A. installing the NVIDIA Container Toolkit on your local machine
- B. Manually creating the AWS EC2 instance with a PostgreSQL database
- C. Adding Amazon Elastic Kubernetes Services (EKS) to your AWS account
- D. Recording the name of a valid AWS EC2 keypair
Answer: D
Explanation:
In order to use the "det deploy" command to set up a cluster for HPE Machine Learning Development Environment (or the open source Determined Al) on Amazon Web Services (AWS), you will need to have a valid AWS EC2 keypair. The keypair will authenticate your access to the cluster and allow you to securely access the cluster once it is set up.
NEW QUESTION 31
You want to set up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined all on a local machine. Which OS Is supported?
- A. HP-UX v11i
- B. Windows Server 2016 or above
- C. Red Hat 7-based Linux
- D. Windows 10 or above
Answer: A
NEW QUESTION 32
Compared to Asynchronous Successive Halving Algorithm (ASHA), what is an advantage of Adaptive ASHA?
- A. Adaptive ASHA tries multiple exploration/exploitation tradeoffs oy running multiple Instances of ASHA.
- B. ASHA selects hyperparameter configs entirely at random while Adaptive ASHA clones higher-performing configs.
- C. Adaptive ASHA can handle hyperparameters related to neural architecture while ASHA cannot.
- D. Adaptive ASHA can train more trials in certain amount of time, as compared to ASHA.
Answer: A
NEW QUESTION 33
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 trial tails, and the ML engineer must restart it manually by re-running the experiment.
- B. The concluded reschedules the trial on another available GPU in the pool, and the trial restarts from the state of the latest training workload.
- C. The conductor reschedules the trial on another available GPU in the pool, and the trial restarts from the latest checkpoint.
- D. The trial fails, and the ML engineer must manually restart it from the latest checkpoint using the WebUI.
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 34
The 10 agents in "my-compute-poor nave 8 GPUs each, you want to change an experiment config to run on multiple GPUs at once. What Is a valid setting for "resources_per_trial?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: D
Explanation:
The valid setting for "resourcespertrial" for the 10 agents in "my-compute-poor" with 8 GPUs each would be 20, as this would be the total number of GPUs available across all 10 agents. This setting would allow the experiment config to run on multiple GPUs at once.
NEW QUESTION 35
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