cs249r_book/mlsysim/vscode-ext

MLSysim Workbench (VS Code Extension)

The MLSysim Workbench is the official Visual Studio Code extension for the MLSys·im analytical modeling framework. It provides a deeply integrated, interactive UI for exploring the Silicon Zoo, running evaluations, and searching the design space without leaving your editor.

Features

• Zoo Explorer: Browse the built-in Hardware and Models registries directly from the sidebar.
• Quick Evaluation: Right-click any hardware or model in the sidebar to run an instant mlsysim eval directly in the integrated terminal.
• YAML Scenario Integration: Right-click any .yaml configuration file to evaluate, optimize, or export schemas.
• Test Runner: Run the full MLSys·im pytest suite or individual test files with one click.
• Action History: Re-run recent evaluations and optimizations from the "Recent Runs" pane.

Requirements

You must have the mlsysim Python package installed in your active environment.

pip install mlsysim

If you are using a virtual environment (venv, conda, etc.), make sure VS Code has the correct Python interpreter selected, or explicitly configure the path in settings.

Extension Settings

This extension contributes the following settings:

• mlsysim.pythonPath: Path to the Python interpreter (default: python3).
• mlsysim.defaultPrecision: Default precision used for Quick Evals (e.g., fp16).
• mlsysim.defaultBatchSize: Default batch size for Quick Evals (default: 1).
• mlsysim.defaultEfficiency: Default MFU efficiency for Quick Evals (default: 0.5).
• mlsysim.outputFormat: The format for CLI output (text, json, markdown).

Building & Installing Locally

To package and install the extension manually:

1. Install vsce globally: npm install -g @vscode/vsce
2. Run npm install inside the vscode-ext directory.
3. Package the extension: vsce package
4. Install the generated .vsix file in VS Code:
   • View -> Command Palette -> Extensions: Install from VSIX...

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Part of the Machine Learning Systems textbook ecosystem.