TheRock/rocm-libraries/projects/hipblas/clients/include/host_strided_batch_matrix.hpp

/* ************************************************************************
 * Copyright (C) 2018-2024 Advanced Micro Devices, Inc. All rights reserved.
 *
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 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
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 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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 * SOFTWARE.
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#pragma once

#include "host_alloc.hpp"

//
// Local declaration of the device strided batch matrix.
//
template <typename T>
class device_strided_batch_matrix;

//!
//! @brief Implementation of a host strided batched matrix.
//!
template <typename T>
class host_strided_batch_matrix
{
public:
    //!
    //! @brief Disallow copying.
    //!
    host_strided_batch_matrix(const host_strided_batch_matrix&) = delete;

    //!
    //! @brief Disallow assigning.
    //!
    host_strided_batch_matrix& operator=(const host_strided_batch_matrix&) = delete;

    //!
    //! @brief Constructor.
    //! @param m           The number of rows of the Matrix.
    //! @param n           The number of cols of the Matrix.
    //! @param lda         The leading dimension of the Matrix.
    //! @param stride The stride.
    //! @param batch_count The batch count.
    //!
    explicit host_strided_batch_matrix(
        size_t m, size_t n, size_t lda, hipblasStride stride, int64_t batch_count)
        : m_m(m)
        , m_n(n)
        , m_lda(lda)
        , m_stride(stride)
        , m_batch_count(batch_count)
        , m_nmemb(calculate_nmemb(n, lda, stride, batch_count))
    {
        bool valid_parameters = this->m_nmemb > 0;
        if(valid_parameters)
        {
            this->m_data = (T*)host_calloc_throw(this->m_nmemb, sizeof(T));
        }
    }

    //!
    //! @brief Destructor.
    //!
    ~host_strided_batch_matrix()
    {
        if(nullptr != this->m_data)
        {
            host_free(this->m_data);
            this->m_data = nullptr;
        }
    }

    //!
    //! @brief Returns the data pointer.
    //!
    T* data()
    {
        return this->m_data;
    }

    //!
    //! @brief Returns the data pointer.
    //!
    const T* data() const
    {
        return this->m_data;
    }

    //!
    //! @brief Returns the rows of the Matrix.
    //!
    size_t m() const
    {
        return this->m_m;
    }

    //!
    //! @brief Returns the cols of the Matrix.
    //!
    size_t n() const
    {
        return this->m_n;
    }

    //!
    //! @brief Returns the leading dimension of the Matrix.
    //!
    size_t lda() const
    {
        return this->m_lda;
    }

    //!
    //! @brief Returns the batch count.
    //!
    int64_t batch_count() const
    {
        return this->m_batch_count;
    }

    //!
    //! @brief Returns the stride.
    //!
    hipblasStride stride() const
    {
        return this->m_stride;
    }

    //!
    //! @brief Returns nmemb.
    //!
    size_t nmemb() const
    {
        return this->m_nmemb;
    }

    //!
    //! @brief Returns pointer.
    //! @param batch_index The batch index.
    //! @return A mutable pointer to the batch_index'th matrix.
    //!
    T* operator[](int64_t batch_index)
    {

        return (this->m_stride >= 0)
                   ? this->m_data + this->m_stride * batch_index
                   : this->m_data + (batch_index + 1 - this->m_batch_count) * this->m_stride;
    }

    //!
    //! @brief Returns non-mutable pointer.
    //! @param batch_index The batch index.
    //! @return A non-mutable mutable pointer to the batch_index'th matrix.
    //!
    const T* operator[](int64_t batch_index) const
    {

        return (this->m_stride >= 0)
                   ? this->m_data + this->m_stride * batch_index
                   : this->m_data + (batch_index + 1 - this->m_batch_count) * this->m_stride;
    }

    //!
    //! @brief Cast operator.
    //! @remark Returns the pointer of the first matrix.
    //!
    operator T*()
    {
        return (*this)[0];
    }

    //!
    //! @brief Non-mutable cast operator.
    //! @remark Returns the non-mutable pointer of the first matrix.
    //!
    operator const T*() const
    {
        return (*this)[0];
    }

    //!
    //! @brief Tell whether resource allocation failed.
    //!
    explicit operator bool() const
    {
        return nullptr != this->m_data;
    }

    //!
    //! @brief Copy data from a strided batched matrix on host.
    //! @param that That strided batched matrix on host.
    //! @return true if successful, false otherwise.
    //!
    bool copy_from(const host_strided_batch_matrix& that)
    {
        if(that.m() == this->m_m && that.n() == this->m_n && that.lda() == this->m_lda
           && that.stride() == this->m_stride && that.batch_count() == this->m_batch_count)
        {
            memcpy(this->data(), that.data(), sizeof(T) * this->m_nmemb);
            return true;
        }
        else
        {
            return false;
        }
    }

    //!
    //! @brief Transfer data from a strided batched matrix on device.
    //! @param that That strided batched matrix on device.
    //! @return The hip error.
    //!
    hipError_t transfer_from(const device_strided_batch_matrix<T>& that)
    {
        hipError_t hip_err;

        if(that.use_HMM && hipSuccess != (hip_err = hipDeviceSynchronize()))
            return hip_err;

        return hipMemcpy(this->m_data,
                         that.data(),
                         sizeof(T) * this->m_nmemb,
                         that.use_HMM ? hipMemcpyHostToHost : hipMemcpyDeviceToHost);
    }

    //!
    //! @brief Check if memory exists.
    //! @return hipSuccess if memory exists, hipErrorOutOfMemory otherwise.
    //!
    hipError_t memcheck() const
    {
        return ((bool)*this) ? hipSuccess : hipErrorOutOfMemory;
    }

private:
    size_t        m_m{};
    size_t        m_n{};
    size_t        m_lda{};
    hipblasStride m_stride{};
    int64_t       m_batch_count{};
    size_t        m_nmemb{};
    T*            m_data{};

    static size_t calculate_nmemb(size_t n, size_t lda, hipblasStride stride, int64_t batch_count)
    {
        return lda * n + size_t(batch_count - 1) * std::abs(stride);
    }
};