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Merge branch 'The-OpenROAD-Project:master' into check-conn-error-config
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name: ORFS variables.yaml tester and linter
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on:
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pull_request:
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jobs:
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docs-test-job:
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name: 'Tests for variables.yaml'
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if: github.event_name == 'pull_request' || github.event_name == 'push'
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Run generate-variables-docs.py
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run: |
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python3 flow/scripts/generate-variables-docs.py
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- name: Check if FlowVariables.md is up to date
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run: |
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git diff --exit-code docs/user/FlowVariables.md
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- name: Run yamlfix check
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run: |
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pip install yamlfix==1.17.0
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yamlfix -c yamlfix.toml flow/scripts/variables.yaml --check

docs/user/FlowVariables.md

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docs/user/InstructionsForAutoTuner.md

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that works in Python3.8 for installation and configuration of AutoTuner,
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as shown below:
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```{note}
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Make sure you run the following commands in the ORFS root directory.
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```
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```shell
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# Install prerequisites
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./tools/AutoTuner/installer.sh
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### General Information
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The `distributed.py` script located in `./tools/AutoTuner/src/autotuner` uses [Ray's](https://docs.ray.io/en/latest/index.html) job scheduling and management to
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The `autotuner.distributed` module uses [Ray's](https://docs.ray.io/en/latest/index.html) job scheduling and management to
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fully utilize available hardware resources from a single server
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configuration, on-premise or over the cloud with multiple CPUs.
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The `sweep` mode is useful when we want to isolate or test a single or very few
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parameters. On the other hand, `tune` is more suitable for finding
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the best combination of a complex and large number of flow
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parameters. Both modes rely on user-specified search space that is
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defined by a `.json` file, they use the same syntax and format,
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though some features may not be available for sweeping.
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parameters.
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```{note}
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The order of the parameters matter. Arguments `--design`, `--platform` and
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`--config` are always required and should precede *mode*.
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```
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```{note}
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The following commands should be run from `./tools/AutoTuner`.
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```
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#### Tune only
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* AutoTuner: `python3 distributed.py tune -h`
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* AutoTuner: `python3 -m autotuner.distributed tune -h`
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Example:
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```shell
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python3 distributed.py --design gcd --platform sky130hd \
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--config ../../../../flow/designs/sky130hd/gcd/autotuner.json \
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python3 -m autotuner.distributed --design gcd --platform sky130hd \
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--config ../../flow/designs/sky130hd/gcd/autotuner.json \
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tune --samples 5
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```
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#### Sweep only
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* Parameter sweeping: `python3 distributed.py sweep -h`
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* Parameter sweeping: `python3 -m autotuner.distributed sweep -h`
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Example:
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```shell
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python3 distributed.py --design gcd --platform sky130hd \
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--config distributed-sweep-example.json \
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python3 -m autotuner.distributed --design gcd --platform sky130hd \
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--config src/autotuner/distributed-sweep-example.json \
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sweep
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```
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env.sh

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export OPENROAD=${DIR}/tools/OpenROAD
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echo "OPENROAD: ${OPENROAD}"
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export PATH=${DIR}/dependencies/bin:$PATH
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export PATH=${DIR}/tools/install/OpenROAD/bin:$PATH
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export PATH=${DIR}/tools/install/yosys/bin:$PATH
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export PATH=${DIR}/dependencies/bin:$PATH
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if [[ "$OSTYPE" == "darwin"* ]]; then
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export PATH="/Applications/KLayout/klayout.app/Contents/MacOS:$PATH"

etc/DependencyInstaller.sh

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source /opt/rh/rh-python38/enable
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set -u
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fi
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local pkgs="pandas numpy firebase_admin click pyyaml"
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local pkgs="pandas numpy firebase_admin click pyyaml yamlfix"
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if [[ $(id -u) == 0 ]]; then
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pip3 install --no-cache-dir -U $pkgs
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else

flow/BUILD.bazel

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