Different readers will approach the documentation with varying requirements and levels of familiarity with ADO. This makes it difficult to provide a single set of ADO commands that suits every use case. Below are two common scenarios and possible approaches:
Case 1 - Readers already familiar with ADO: These users are typically capable of configuring and validating their own benchmarks. For this audience, a brief reminder together with a link to the ADO documentation should be sufficient.
Case 2 - Readers with no prior ADO experience: For users new to both Nexus and ADO:
- The project already provides examples that can serve as a starting point (for example, the Random Walk example: https://ibm.github.io/ado/examples/random-walk/).
- If an example is added to the Nexus project, it should be fully self-contained and executable from start to finish, allowing users to reproduce the workflow
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## Step 4: Run the benchmark |
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Install the benchmark package and run the benchmark instance locally using the |
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`ado` CLI. First save the following operation configuration to a file `op.yaml`. |
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It will execute the experiment on all points in your space. |
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```yaml |
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metadata: |
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name: randomwalk-all |
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spaces: |
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- dynamically_inserted |
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operation: |
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module: |
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operatorName: random_walk |
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operationType: search |
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parameters: |
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numberEntities: all |
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samplerConfig: |
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samplerType: generator |
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mode: random |
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``` |
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Then, |
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```bash |
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uv pip install packages/<package-name>/benchmark_packages/<experiment-package-name> |
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ado create space -f <space-yaml-path> |
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ado create operation -f op.yaml --use-latest space |
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``` |
Different readers will approach the documentation with varying requirements and levels of familiarity with ADO. This makes it difficult to provide a single set of ADO commands that suits every use case. Below are two common scenarios and possible approaches:
Case 1 - Readers already familiar with ADO: These users are typically capable of configuring and validating their own benchmarks. For this audience, a brief reminder together with a link to the ADO documentation should be sufficient.
Case 2 - Readers with no prior ADO experience: For users new to both Nexus and ADO:
algorithm-nexus/docs/contributing/add_benchmark.md
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