The NVIDIA CUDA Basic Linear Algebra Subroutines (cuBLAS) library is a GPU-accelerated version of the complete standard BLAS library with 152 standard BLAS routines. A basic description of the library together with basic performance comparisons with MKL can be found [here](https://developer.nvidia.com/cublas"Nvidia cuBLAS").
The NVIDIA CUDA Basic Linear Algebra Subroutines (cuBLAS) library is a GPU-accelerated version of the complete standard BLAS library with 152 standard BLAS routines. A basic description of the library together with basic performance comparisons with MKL can be found [here][a].
#### cuBLAS Example: SAXPY
The SAXPY function multiplies the vector x by the scalar alpha, and adds it to the vector y, overwriting the latest vector with the result. A description of the cuBLAS function can be found in [NVIDIA CUDA documentation](http://docs.nvidia.com/cuda/cublas/index.html#cublas-lt-t-gt-axpy"Nvidia CUDA documentation "). Code can be pasted in the file and compiled without any modification.
The SAXPY function multiplies the vector x by the scalar alpha, and adds it to the vector y, overwriting the latest vector with the result. A description of the cuBLAS function can be found in [NVIDIA CUDA documentation][b]. Code can be pasted in the file and compiled without any modification.
```cpp
/* Includes, system */
...
...
@@ -283,8 +283,8 @@ int main(int argc, char **argv)
!!! note
cuBLAS has its own function for data transfers between CPU and GPU memory:
-[cublasSetVector](http://docs.nvidia.com/cuda/cublas/index.html#cublassetvector) - transfers data from CPU to GPU memory
-[cublasGetVector](http://docs.nvidia.com/cuda/cublas/index.html#cublasgetvector) - transfers data from GPU to CPU memory
-[cublasSetVector][c] - transfers data from CPU to GPU memory
-[cublasGetVector][d] - transfers data from GPU to CPU memory
To compile the code using the NVCC compiler a "-lcublas" compiler flag has to be specified:
