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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 15, 02:15 UTC

Fix bullets in incremental_build.md (#20642)

Michael Goin committed Jul 9, 2025 at 12:03 UTC 9e0ef888f0f1d39802dd0039064bb88a6918b320
1 file changed +1
docs/contributing/incremental_build.md
+1
@@ -84,6 +84,7 @@ Below is an example of what the generated `CMakeUserPresets.json` might look lik
84 ```
85
86 **What do the various configurations mean?**
87 +
88 - `CMAKE_CUDA_COMPILER`: Path to your `nvcc` binary. The script attempts to find this automatically.
89 - `CMAKE_C_COMPILER_LAUNCHER`, `CMAKE_CXX_COMPILER_LAUNCHER`, `CMAKE_CUDA_COMPILER_LAUNCHER`: Setting these to `ccache` (or `sccache`) significantly speeds up rebuilds by caching compilation results. Ensure `ccache` is installed (e.g., `sudo apt install ccache` or `conda install ccache`). The script sets these by default.
90 - `VLLM_PYTHON_EXECUTABLE`: Path to the Python executable in your vLLM development environment. The script will prompt for this, defaulting to the current Python environment if suitable.