How to work with Eigen in CUDA kernels

Question

Eigen is a c++ linear algebra library http://eigen.tuxfamily.org.

It\'s easy to work with basic data types, like basic float arrays, and just copy it to device memory an

Answer 1

Since November 2016 (Release of Eigen 3.3), a new option exists: Using Eigen directly inside CUDA kernels - see this question.

Example from the linked question:

__global__ void cu_dot(Eigen::Vector3f *v1, Eigen::Vector3f *v2, double *out, size_t N)
{
    int idx = blockIdx.x * blockDim.x + threadIdx.x;
    if(idx < N)
    {
        out[idx] = v1[idx].dot(v2[idx]);
    }
    return;
}

Copying an array of Eigen::Vector3f to device:

Eigen::Vector3f *host_vectors = new Eigen::Vector3f[N];
Eigen::Vector3f *dev_vectors;
cudaMalloc((void **)&dev_vectors, sizeof(Eigen::Vector3f)*N)
cudaMemcpy(dev_vectors, host_vectors, sizeof(Eigen::Vector3f)*N, cudaMemcpyHostToDevice)