RandomMatrix.cuh File Reference

Classes
class	GaussianRandomMatrixGenerator_GPU< Derived, >

Functions
template<class Derived1 , class Derived2 , class Derived3 , typename std::enable_if_t< std::is_convertible_v< Derived3, OperatorSpaceBase< Derived3 > > > * = nullptr>
__global__ void	RandomMatrixGenerator_sample_kernel (Eigen::MatrixBase< Derived1 > *samplePtr, Eigen::DenseBase< Derived2 > const *coeffPtr, OperatorSpaceBase< Derived3 > const *opSpacePtr)

Function Documentation

RandomMatrixGenerator_sample_kernel()

template<class Derived1 , class Derived2 , class Derived3 , typename std::enable_if_t< std::is_convertible_v< Derived3, OperatorSpaceBase< Derived3 > > > * = nullptr>

__global__ void RandomMatrixGenerator_sample_kernel	(	Eigen::MatrixBase< Derived1 > *	samplePtr,
		Eigen::DenseBase< Derived2 > const *	coeffPtr,
		OperatorSpaceBase< Derived3 > const *	opSpacePtr
	)

                                                                                                   {
    using RealScalar   = typename Derived1::RealScalar;
 
    int const  opId    = blockIdx.x * blockDim.x + threadIdx.x;
    int const  basisId = blockIdx.y * blockDim.y + threadIdx.y;
    auto const opDim   = opSpacePtr->dim();
    auto const baseDim = opSpacePtr->baseDim();
    if(opId >= opDim) return;
    if(basisId >= baseDim) return;
 
    auto const coeff    = (*coeffPtr)(opId);
    auto const [k, val] = opSpacePtr->action(opId, basisId);
    auto& matelemRef    = reinterpret_cast<RealScalar(&)[2]>((*samplePtr)(k, basisId));
 
    atomicAdd(&matelemRef[0], coeff * val.real());
    atomicAdd(&matelemRef[1], coeff * val.imag());
    return;
}