point(x,y)的索引位置是: y * width + x 这个是Heterogeneous Parallel Programming lab4:Basic Matrix Matrix Multiplication的代码: View Code
// Forward declaration of the matrix multiplication kernel __global__ void MatMulKernel(const Matrix, const Matrix, Matrix); // Matrix multiplication - Host code // Matrix dimensions are assumed to be multiples of BLOCK_SIZE void MatMul(const Matrix A, const Matrix B, Matrix C) { // Load...
// Forward declaration of the matrix multiplication kernel __global__ void MatMulKernel(const Matrix, const Matrix, Matrix); // Matrix multiplication - Host code // Matrix dimensions are assumed to be multiples of BLOCK_SIZE void MatMul(const Matrix A, const Matrix B, Matrix C) { // Load...
Matrix-matrix multiplication Matrix multiplication with multiple right hand sides Parallel prefix sum of large arrays Any many more! Performance measurement and optimization Bandwidth tests Application profiling using timers Advanced application examples ...
/* Matrix multiplication: C = A * B. * Host code. * * This sample revisitsmatrix multiplicationwith CUDA task. The code of matrix * multiplication is exactly the same as in matrixMulDrv sample of this SDK. * This sample, however, demonstrates how to link CUDA driver at runtime and ...
(const Matrix, const Matrix, Matrix); // Matrix multiplication - Host code // Matrix dimensions are assumed to be multiples of BLOCK_SIZE void MatMul(const Matrix A, const Matrix B, Matrix C) { // Load A and B to device memory Matrix d_A; d_A.width = A.width; d_A.height = ...
// Matrix multiplication - Host code // Matrix dimensions are assumed to be multiples of BLOCK_SIZE void MatMul(const Matrix A, const Matrix B, Matrix C) { // Load A and B to device memory Matrix d_A; d_A.width = A.width; d_A.height = A.height; ...
通用矩阵乘法 (General Matrix Multiplication,GEMM) 是各种模型和计算中的核心部分,同时也是评估计算硬件性能 (FLOPS) 的标准技术。本文将通过对 GEMM 的实现和优化,来试图理解高性能计算和软硬件系统。 一、GEMM的基本特征 1.1 GEMM计算过程及复杂度
( out: *mut c_float, a: *const c_float, b: *const c_float, m: size_t, n: size_t, k: size_t, ); fn _init_cublas; fn _destory_cublas; } // Function to perform matrix multiplication using the cuBLAS library. pub fn matmul<D1: Dimension, D2: Dimension, D3: Dimension>( ...
通用矩阵乘法 (General Matrix Multiplication,GEMM) 是各种模型和计算中的核心部分,同时也是评估计算硬件性能 (FLOPS) 的标准技术。本文将通过对 GEMM 的实现和优化,来试图理解高性能计算和软硬件系统。 一、GEMM的基本特征 1.1 GEMM计算过程及复杂度