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

A.
Experiment tracking
A.
Experiment tracking
Answers
B.
Model Inferencing
B.
Model Inferencing
Answers
C.
Distributed training
C.
Distributed training
Answers
D.
Premium dedicated support
D.
Premium dedicated support
Answers
Suggested answer: A

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
A.
Letting the conductor automatically determine which servers to use for each experiment, based on the number of resource slots required
Answers
B.
Deploying two HPE Machine Learning Development Environment clusters, one tor each server type
B.
Deploying two HPE Machine Learning Development Environment clusters, one tor each server type
Answers
C.
Deploying servers with 8 GPUs as agents and using the conductor to run experiments that require only 2 GPUs
C.
Deploying servers with 8 GPUs as agents and using the conductor to run experiments that require only 2 GPUs
Answers
D.
Establishing multiple compute resource pools on the cluster, one tor servers or each type
D.
Establishing multiple compute resource pools on the cluster, one tor servers or each type
Answers
Suggested answer: D

Compared to Asynchronous Successive Halving Algorithm (ASHA), what is an advantage of Adaptive ASHA?

A.
Adaptive ASHA can handle hyperparameters related to neural architecture while ASHA cannot.
A.
Adaptive ASHA can handle hyperparameters related to neural architecture while ASHA cannot.
Answers
B.
ASHA selects hyperparameter configs entirely at random while Adaptive ASHA clones higherperforming configs.
B.
ASHA selects hyperparameter configs entirely at random while Adaptive ASHA clones higherperforming configs.
Answers
C.
Adaptive ASHA can train more trials in certain amount of time, as compared to ASHA.
C.
Adaptive ASHA can train more trials in certain amount of time, as compared to ASHA.
Answers
D.
Adaptive ASHA tries multiple exploration/exploitation tradeoffs oy running multiple Instances of ASHA.
D.
Adaptive ASHA tries multiple exploration/exploitation tradeoffs oy running multiple Instances of ASHA.
Answers
Suggested answer: D

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

A.
It uses a centralized training architecture that is highly efficient.
A.
It uses a centralized training architecture that is highly efficient.
Answers
B.
It helps DL projects complete faster for a faster ROI.
B.
It helps DL projects complete faster for a faster ROI.
Answers
C.
It helps companies deploy models and generate revenue.
C.
It helps companies deploy models and generate revenue.
Answers
D.
It automatically cleans up data to create better end results.
D.
It automatically cleans up data to create better end results.
Answers
Suggested answer: B

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.
In the experiment config that you used, look for the "bucket" field under "hyperparameters." This is the UUID for checkpoints.
A.
In the experiment config that you used, look for the "bucket" field under "hyperparameters." This is the UUID for checkpoints.
Answers
B.
Use the "det experiment download -top-n I" command, referencing the experiment ID.
B.
Use the "det experiment download -top-n I" command, referencing the experiment ID.
Answers
C.
In the Web Ul, go to the Task page and click the checkpoint task that has the experiment ID.
C.
In the Web Ul, go to the Task page and click the checkpoint task that has the experiment ID.
Answers
D.
Look for a "determined-checkpoint/" bucket within Amazon S3, referencing your experiment ID.
D.
Look for a "determined-checkpoint/" bucket within Amazon S3, referencing your experiment ID.
Answers
Suggested answer: B

What is a reason to use the best tit policy on an HPE Machine Learning Development Environment resource pool?

A.
Ensuring that all experiments receive their fair share of resources
A.
Ensuring that all experiments receive their fair share of resources
Answers
B.
Minimizing costs in a cloud environment
B.
Minimizing costs in a cloud environment
Answers
C.
Equally distributing utilization across multiple agents
C.
Equally distributing utilization across multiple agents
Answers
D.
Ensuring that the highest priority experiments obtain access to more resources
D.
Ensuring that the highest priority experiments obtain access to more resources
Answers
Suggested answer: B

What is one of the responsibilities of the conductor of an HPE Machine Learning Development Environment cluster?

A.
it downloads datasets for training.
A.
it downloads datasets for training.
Answers
B.
It uploads model checkpoints.
B.
It uploads model checkpoints.
Answers
C.
It validates trained models.
C.
It validates trained models.
Answers
D.
It ensures experiment metadata is stored.
D.
It ensures experiment metadata is stored.
Answers
Suggested answer: B

What type of interconnect does HPE Machine learning Development System use for high-speed, agent-to-agent communications?

A.
Remote Direct Memory Access (RDMA) overconverged Ethernet (RoCE)
A.
Remote Direct Memory Access (RDMA) overconverged Ethernet (RoCE)
Answers
B.
Slingshot
B.
Slingshot
Answers
C.
InfiniBand
C.
InfiniBand
Answers
D.
Data Center Bridging (OCB)-enabled Ethernet
D.
Data Center Bridging (OCB)-enabled Ethernet
Answers
Suggested answer: D

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.
A.
Adjusting how many of the latest and best checkpoints are saved in the experiment config's checkpoint storage settings.
Answers
B.
Monitoring ongoing trials In the WebUl and clicking checkpoint nags to auto-save the desired checkpoints.
B.
Monitoring ongoing trials In the WebUl and clicking checkpoint nags to auto-save the desired checkpoints.
Answers
C.
Double-checking that the checkpoint storage location is operating under 90% of total capacity.
C.
Double-checking that the checkpoint storage location is operating under 90% of total capacity.
Answers
D.
Adjusting the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage.
D.
Adjusting the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage.
Answers
Suggested answer: D

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.
10
A.
10
Answers
B.
24
B.
24
Answers
C.
12
C.
12
Answers
D.
20
D.
20
Answers
Suggested answer: A
Total 40 questions
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