cpp_integration

Integrating Skala in C++ code

This example demonstrates how to use the Skala machine learning functional in C++ CPU applications using LibTorch.

Setup environment

Install the locked Pixi environment from the repository root:

pixi install --locked -e cpp-integration

Build library

Configure and build the example with CMake and Ninja in the Pixi environment:

pixi run -e cpp-integration cmake -B build_example -S model/examples/cpp/cpp_integration -G Ninja
pixi run -e cpp-integration cmake --build build_example

Run example

Download the Skala model from Hugging Face:

pixi run -e cpp-integration hf download microsoft/skala-1.1 \
	skala-1.1-rev1.fun --local-dir .

Prepare the molecular features for a test molecule (H2) using the provided script:

pixi run -e default python examples/cpp/cpp_integration/prepare_inputs.py \
	--output-dir features

Finally, run $E_\text{xc}$ and (partial) $V_\text{xc}$ computations with the C++ example:

pixi run -e cpp-integration ./build_example/skala_cpp_integration ./skala-1.1-rev1.fun ./features

Note: You are expected to add D3 dispersion correction (using b3lyp settings) to the final energy of Skala.

Performance tuning

This guide from Intel provides useful tips on how to tune performance of PyTorch models on CPU.