GaussianRandomMatrixGenerator_GPU< Derived, > Class Template Reference

Collaboration diagram for GaussianRandomMatrixGenerator_GPU< Derived, >:

Public Member Functions
	GaussianRandomMatrixGenerator_GPU (Derived const &opSpace, int seed=0, RealScalar stddev=1.0)
	GaussianRandomMatrixGenerator_GPU ()=default
	Default constructor.
	GaussianRandomMatrixGenerator_GPU (GaussianRandomMatrixGenerator_GPU const &other)=delete
	Copy constructor.
	GaussianRandomMatrixGenerator_GPU (GaussianRandomMatrixGenerator_GPU &&other)=default
	Move constructor.
	~GaussianRandomMatrixGenerator_GPU ()=default
	Destructor.
Operator overloads
__host__ __device__ GaussianRandomMatrixGenerator_GPU &	operator= (GaussianRandomMatrixGenerator_GPU const &other)=delete
	Copy assignment operator.
__host__ __device__ GaussianRandomMatrixGenerator_GPU &	operator= (GaussianRandomMatrixGenerator_GPU &&other)=default
	Move assignment operator.
void	reset ()
void	discard (unsigned long long num)
	Discards random numbers to advance internal states of the random number generator.
ObjectOnGPU< Eigen::MatrixX< Scalar > >	operator() ()
	Generates an instance of a random matrix.
ObjectOnGPU< Eigen::MatrixX< Scalar > >	sample ()
	Generates an instance of a random matrix.

Private Types
using	Scalar = typename Derived::Scalar
using	RealScalar = typename Eigen::NumTraits< typename Derived::Scalar >::Real

Private Attributes
ObjectOnGPU< Derived >	m_opSpace = ObjectOnGPU<Derived>(Derived())
int	m_seed
std::mt19937	mt
std::normal_distribution< double >	Gaussian
unsigned long long	count

Member Typedef Documentation

RealScalar

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

using GaussianRandomMatrixGenerator_GPU< Derived, >::RealScalar = typename Eigen::NumTraits<typename Derived::Scalar>::Real

private

Scalar

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

using GaussianRandomMatrixGenerator_GPU< Derived, >::Scalar = typename Derived::Scalar

private

Constructor & Destructor Documentation

GaussianRandomMatrixGenerator_GPU() [1/4]

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

GaussianRandomMatrixGenerator_GPU< Derived, >::GaussianRandomMatrixGenerator_GPU ( Derived const &  opSpace, int  seed = 0, RealScalar  stddev = 1.0  )

inline

            : m_opSpace{opSpace}, m_seed(seed), mt(seed), Gaussian{0.0, stddev}, count{0} {}

GaussianRandomMatrixGenerator_GPU() [2/4]

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

GaussianRandomMatrixGenerator_GPU< Derived, >::GaussianRandomMatrixGenerator_GPU ( )

default

Default constructor.

GaussianRandomMatrixGenerator_GPU() [3/4]

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

GaussianRandomMatrixGenerator_GPU< Derived, >::GaussianRandomMatrixGenerator_GPU ( GaussianRandomMatrixGenerator_GPU< Derived, > const &  other )

delete

Copy constructor.

Parameters

other

GaussianRandomMatrixGenerator_GPU() [4/4]

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

GaussianRandomMatrixGenerator_GPU< Derived, >::GaussianRandomMatrixGenerator_GPU ( GaussianRandomMatrixGenerator_GPU< Derived, > &&  other )

default

Move constructor.

Parameters

other

~GaussianRandomMatrixGenerator_GPU()

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

GaussianRandomMatrixGenerator_GPU< Derived, >::~GaussianRandomMatrixGenerator_GPU ( )

default

Destructor.

Member Function Documentation

discard()

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

void GaussianRandomMatrixGenerator_GPU< Derived, >::discard ( unsigned long long  num )

inline

Discards random numbers to advance internal states of the random number generator.

Parameters

num	Number of random numbers to be discarded

                                             {
            for(auto j = 0; j < num * m_opSpace.dim(); ++j) Gaussian(mt);
            count += num * m_opSpace.dim();
        }

operator()()

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

ObjectOnGPU< Eigen::MatrixX< Scalar > > GaussianRandomMatrixGenerator_GPU< Derived, >::operator() ( )

inline

Generates an instance of a random matrix.

Parameters

[out]

mat

Matrix to which the generated matrix is assigned

{ return this->sample(); }

operator=() [1/2]

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

__host__ __device__ GaussianRandomMatrixGenerator_GPU & GaussianRandomMatrixGenerator_GPU< Derived, >::operator= ( GaussianRandomMatrixGenerator_GPU< Derived, > &&  other )

default

Move assignment operator.

Parameters

other

operator=() [2/2]

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

__host__ __device__ GaussianRandomMatrixGenerator_GPU & GaussianRandomMatrixGenerator_GPU< Derived, >::operator= ( GaussianRandomMatrixGenerator_GPU< Derived, > const &  other )

delete

Copy assignment operator.

Parameters

other

reset()

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

void GaussianRandomMatrixGenerator_GPU< Derived, >::reset ( )

inline

{ mt = std::mt19937(m_seed); }

sample()

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

ObjectOnGPU< Eigen::MatrixX< Scalar > > GaussianRandomMatrixGenerator_GPU< Derived, >::sample ( )

inline

Generates an instance of a random matrix.

Returns

ObjectOnGPU< Eigen::MatrixX<Scalar> >

                                                     {
            using Scalar     = typename Derived::Scalar;
            using RealScalar = typename Eigen::NumTraits<typename Derived::Scalar>::Real;
 
            ObjectOnGPU< Eigen::MatrixX<Scalar> > sample(m_opSpace.baseDim(), m_opSpace.baseDim());
            Eigen::VectorX<RealScalar> coeff = Eigen::VectorXd::NullaryExpr(m_opSpace.dim(), [&]() {
                                                   return Gaussian(mt);
                                               }).template cast<RealScalar>();
            ObjectOnGPU< decltype(coeff) > dCoeff(coeff);
 
            //
            // Configure Threads and Grids here
            //
            constexpr void (*kernel)(
                Eigen::MatrixBase< std::remove_reference_t<decltype(*sample.ptr())> >*,
                Eigen::DenseBase< std::remove_reference_t<decltype(*dCoeff.ptr())> > const*,
                OperatorSpaceBase< std::remove_reference_t<decltype(*m_opSpace.ptr())> > const*)
                = &RandomMatrixGenerator_sample_kernel;
            struct cudaFuncAttributes attr;
            cuCHECK(cudaFuncGetAttributes(&attr, kernel));
            dim3 nThread;
            nThread.x = min((size_t)m_opSpace.dim(), (size_t)sqrt(attr.maxThreadsPerBlock));
            nThread.y = min((size_t)m_opSpace.baseDim(), (size_t)sqrt(attr.maxThreadsPerBlock));
            auto upperQuotient
                = [](size_t const& x, size_t const& y) { return (x % y == 0 ? x / y : x / y + 1); };
            dim3 nBlock;
            nBlock.x = upperQuotient(m_opSpace.dim(), nThread.x);
            nBlock.y = upperQuotient(m_opSpace.baseDim(), nThread.y);
 
            kernel<<<nBlock, nThread>>>(sample.ptr(), dCoeff.ptr(), m_opSpace.ptr());
            cuCHECK(cudaDeviceSynchronize());
            return sample;
        };

Member Data Documentation

count

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

unsigned long long GaussianRandomMatrixGenerator_GPU< Derived, >::count

mutableprivate

Gaussian

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

std::normal_distribution<double> GaussianRandomMatrixGenerator_GPU< Derived, >::Gaussian

private

m_opSpace

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

ObjectOnGPU<Derived> GaussianRandomMatrixGenerator_GPU< Derived, >::m_opSpace = ObjectOnGPU<Derived>(Derived())

private

m_seed

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

int GaussianRandomMatrixGenerator_GPU< Derived, >::m_seed

private

mt

template<class Derived , typename std::enable_if_t< std::is_convertible_v< Derived, OperatorSpaceBase< Derived > > > * = nullptr>

std::mt19937 GaussianRandomMatrixGenerator_GPU< Derived, >::mt

private

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The documentation for this class was generated from the following file:

• /Users/shoki/GitHub/Locality/Headers/HilbertSpace/RandomMatrix.cuh