FullMatCUDA.hpp

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/*******************************************************************************
 * Copyright (C) 2017-2025 Theodore Chang
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program.  If not, see <http://www.gnu.org/licenses/>.
 ******************************************************************************/
// ReSharper disable CppCStyleCast
#ifndef FULLMATCUDA_HPP
#define FULLMATCUDA_HPP
 
#include <cuda_runtime.h>
#include <cusolverDn.h>
#include "FullMat.hpp"
 
template<sp_d T> class FullMatCUDA final : public FullMat<T> {
    cusolverDnHandle_t handle = nullptr;
    cudaStream_t stream = nullptr;
 
    int* info = nullptr;
    int* ipiv = nullptr;
    void* d_A = nullptr;
    void* buffer = nullptr;
 
    void acquire() {
        cusolverDnCreate(&handle);
        cudaStreamCreate(&stream);
        cusolverDnSetStream(handle, stream);
 
        cudaMalloc(&info, sizeof(int));
        cudaMemset(info, 0, sizeof(int));
        cudaMalloc(&ipiv, sizeof(int) * this->n_rows);
 
        int bufferSize = 0;
        if constexpr(std::is_same_v<T, float>) {
            cudaMalloc(&d_A, sizeof(float) * this->n_elem);
            cusolverDnSgetrf_bufferSize(handle, static_cast<int>(this->n_rows), static_cast<int>(this->n_cols), (float*)d_A, static_cast<int>(this->n_elem), &bufferSize);
            cudaMalloc(&buffer, sizeof(float) * bufferSize);
        }
        else if(Precision::MIXED == this->setting.precision) {
            cudaMalloc(&d_A, sizeof(float) * this->n_elem);
            cusolverDnSgetrf_bufferSize(handle, static_cast<int>(this->n_rows), static_cast<int>(this->n_cols), (float*)d_A, static_cast<int>(this->n_elem), &bufferSize);
            cudaMalloc(&buffer, sizeof(float) * bufferSize);
        }
        else {
            cudaMalloc(&d_A, sizeof(double) * this->n_elem);
            cusolverDnDgetrf_bufferSize(handle, static_cast<int>(this->n_rows), static_cast<int>(this->n_cols), (double*)d_A, static_cast<int>(this->n_elem), &bufferSize);
            cudaMalloc(&buffer, sizeof(double) * bufferSize);
        }
    }
 
    void release() const {
        if(handle) cusolverDnDestroy(handle);
        if(stream) cudaStreamDestroy(stream);
 
        if(info) cudaFree(info);
        if(d_A) cudaFree(d_A);
        if(buffer) cudaFree(buffer);
        if(ipiv) cudaFree(ipiv);
    }
 
protected:
    int direct_solve(Mat<T>& X, Mat<T>&& B) override { return this->direct_solve(X, B); }
 
    int direct_solve(Mat<T>&, const Mat<T>&) override;
 
public:
    FullMatCUDA(const uword in_rows, const uword in_cols)
        : FullMat<T>(in_rows, in_cols) { acquire(); }
 
    FullMatCUDA(const FullMatCUDA& other)
        : FullMat<T>(other) { acquire(); }
 
    FullMatCUDA(FullMatCUDA&&) noexcept = delete;
    FullMatCUDA& operator=(const FullMatCUDA&) = delete;
    FullMatCUDA& operator=(FullMatCUDA&&) noexcept = delete;
 
    ~FullMatCUDA() override { release(); }
 
    unique_ptr<MetaMat<T>> make_copy() override { return std::make_unique<FullMatCUDA>(*this); }
};
 
template<sp_d T> int FullMatCUDA<T>::direct_solve(Mat<T>& X, const Mat<T>& B) {
    if constexpr(std::is_same_v<T, float>) {
        // pure float
        if(!this->factored) {
            this->factored = true;
            cudaMemcpyAsync(d_A, this->memptr(), sizeof(float) * this->n_elem, cudaMemcpyHostToDevice, stream);
            cusolverDnSgetrf(handle, static_cast<int>(this->n_rows), static_cast<int>(this->n_cols), (float*)d_A, static_cast<int>(this->n_rows), (float*)buffer, ipiv, info);
        }
 
        const size_t byte_size = sizeof(float) * B.n_elem;
 
        void* d_x = nullptr;
        cudaMalloc(&d_x, byte_size);
        cudaMemcpyAsync(d_x, B.memptr(), byte_size, cudaMemcpyHostToDevice, stream);
        cusolverDnSgetrs(handle, CUBLAS_OP_N, static_cast<int>(this->n_rows), static_cast<int>(B.n_cols), (float*)d_A, static_cast<int>(this->n_rows), ipiv, (float*)d_x, static_cast<int>(this->n_rows), info);
 
        X.set_size(arma::size(B));
 
        cudaMemcpyAsync(X.memptr(), d_x, byte_size, cudaMemcpyDeviceToHost, stream);
 
        cudaDeviceSynchronize();
 
        if(d_x) cudaFree(d_x);
    }
    else if(Precision::MIXED == this->setting.precision) {
        // mixed precision
        if(!this->factored) {
            this->factored = true;
            this->s_memory = this->to_float();
            cudaMemcpyAsync(d_A, this->s_memory.memptr(), sizeof(float) * this->s_memory.n_elem, cudaMemcpyHostToDevice, stream);
            cusolverDnSgetrf(handle, static_cast<int>(this->n_rows), static_cast<int>(this->n_cols), (float*)d_A, static_cast<int>(this->n_rows), (float*)buffer, ipiv, info);
        }
 
        const size_t byte_size = sizeof(float) * B.n_elem;
 
        void* d_x = nullptr;
        cudaMalloc(&d_x, byte_size);
 
        X = arma::zeros(B.n_rows, B.n_cols);
 
        mat full_residual = B;
 
        auto multiplier = norm(full_residual);
 
        auto counter = std::uint8_t{0};
        while(counter++ < this->setting.iterative_refinement) {
            if(multiplier < this->setting.tolerance) break;
 
            auto residual = conv_to<fmat>::from(full_residual / multiplier);
 
            cudaMemcpyAsync(d_x, residual.memptr(), byte_size, cudaMemcpyHostToDevice, stream);
            cusolverDnSgetrs(handle, CUBLAS_OP_N, static_cast<int>(this->n_rows), static_cast<int>(B.n_cols), (float*)d_A, static_cast<int>(this->n_rows), ipiv, (float*)d_x, static_cast<int>(this->n_rows), info);
            cudaMemcpyAsync(residual.memptr(), d_x, byte_size, cudaMemcpyDeviceToHost, stream);
 
            cudaDeviceSynchronize();
 
            const mat incre = multiplier * conv_to<mat>::from(residual);
 
            X += incre;
 
            suanpan_debug("Mixed precision algorithm multiplier: {:.5E}.\n", multiplier = arma::norm(full_residual -= this->operator*(incre)));
        }
 
        if(d_x) cudaFree(d_x);
    }
    else {
        // pure double
        if(!this->factored) {
            this->factored = true;
            cudaMemcpyAsync(d_A, this->memptr(), sizeof(double) * this->n_elem, cudaMemcpyHostToDevice, stream);
            cusolverDnDgetrf(handle, static_cast<int>(this->n_rows), static_cast<int>(this->n_cols), (double*)d_A, static_cast<int>(this->n_rows), (double*)buffer, ipiv, info);
        }
 
        const size_t byte_size = sizeof(double) * B.n_elem;
 
        void* d_x = nullptr;
        cudaMalloc(&d_x, byte_size);
        cudaMemcpyAsync(d_x, B.memptr(), byte_size, cudaMemcpyHostToDevice, stream);
        cusolverDnDgetrs(handle, CUBLAS_OP_N, static_cast<int>(this->n_rows), static_cast<int>(B.n_cols), (double*)d_A, static_cast<int>(this->n_rows), ipiv, (double*)d_x, static_cast<int>(this->n_rows), info);
 
        X.set_size(arma::size(B));
 
        cudaMemcpyAsync(X.memptr(), d_x, byte_size, cudaMemcpyDeviceToHost, stream);
 
        cudaDeviceSynchronize();
 
        if(d_x) cudaFree(d_x);
    }
 
    return 0;
}
 
#endif