add build instructions for blas and cublas

BUILD.md

@@ -50,3 +50,26 @@ Where:
 - *codegen* is a command line tool for testing out prompts in a lightweight way (a lot like llama.cpp)
 - *codegen-serve* is the actual REST server that can be used to connect to VSCode
 - *codegen-quantize* is the tool for quantizing models exported by the conversion script. For more details see [Converting and Quantizing The Models](https://github.com/ravenscroftj/turbopilot/wiki/Converting-and-Quantizing-The-Models).
+
+### Building with OpenBLAS
+
+
+[BLAS](https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) libraries accelerate mathematical operations. You can use the OpenBLAS implementation with Turbopilot to make generation faster - particularly for longer prompts.
+
+When you run cmake, you can additionally set `-D GGML_OPENBLAS=On` to enable BLAS support.
+
+E.g. `cmake .. -D GGML_OPENBLAS=On`
+
+### Building with CuBLAS
+
+CuBLAS is the [BLAS](https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) library provided by nvidia that runs linear algebra code on your GPU. This can speed up the application significantly, especially when working with long prompts.
+
+#### Install Cuda SDK for your Operating System
+
+You will need `nvcc` and the `libcublas-dev` dependencies as a bare minimum. Follow the guide from nvidia [here](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) for more detailed installation instructions.
+
+#### Configuring Cmake with CuBLAS
+
+You will need to set `-DGGML_CUBLAS=ON` and also pass the path to your `nvcc` executable with `-DCMAKE_CUDA_COMPILER=/path/to/nvcc`.
+
+Full example: `cmake -DGGML_CUBLAS=ON -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc ..`