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Clara Deploy Hardware Qualification Suite Pipeline [Deprecated]

Clara Deploy Hardware Qualification Suite Pipeline [Deprecated]

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Description
Clara Deploy Hardware Qualification Suite
Publisher
NVIDIA
Latest Tag
0.8.1-2108.1
Modified
April 4, 2023
Compressed Size
113.54 MB
Multinode Support
No
Multi-Arch Support
No
0.8.1-2108.1 (Latest) Security Scan Results

Linux / amd64

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Clara Deploy SDK is being consolidated into Clara Holoscan SDK

More info https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/collections/claradeploy

Clara Hardware Qualification Suite

This asset requires the Clara Deploy SDK. Follow the instructions on the Clara Ansible page to install the Clara Deploy SDK.

Overview

The Clara Hardware Qualification Suite is a benchmarking and scoring utility that can be used to validate that hardware meets the minimum requirements for Clara. It can also help diagnose run-time performance issues.

Set of metrics calculated

Information Tests

  • NVIDIA Driver details
  • GPU information
  • CPU information
  • System-memory capacity and availability
  • Persistent-storage capacity and availability

Exercise Tests

  • System-memory read/write performance
  • CPU computational performance (single thread)
  • CPU computational performance (multi-threaded)
  • Persistent storage read/write performance
  • GPU compute performance

Running the Qualification Suite Inside a Container

sudo docker run -it --rm -v `pwd`:/output --name clara-hqs clara-hqs[:version]

# or, you can add `--entrypoint "./run -i -m -s -g -c single multi -e"` in the above command after `--rm`

# usage: ./run [-h] [-i] [-e] [-m] [-c args [args ...]] [-s] [-g]
# [-d ]

# optional arguments:
# -h, --help show this help message and exit
# -i, --info get hardware information
# -e, --export export output to a json file
# -m, --memory get memory read write performance
# -c args [args ...], --cpu args [args ...]
# get cpu performance by specifying space separated list
# of types of threading [args: single, multi]
# -s, --storage get Persistent storage read write performance
# -g, --gpu get gpu performance
# -d , --dir 
# cuda toolkit samples directory

License

An End User License Agreement is included with the product. By pulling and using the Clara Deploy asset on NGC, you accept the terms and conditions of these licenses.

Suggested Reading

Release notes, the Getting Started Guide, and the SDK itself are available at the NVIDIA Developer forum.

For answers to any questions you may have about this release, visit the NVIDIA Devtalk forum.