mingfeima

Part I: Memory Formats and Channels Last Optimization

(Training material on pytorch CPU performance optimization)

• Part II: Parallelization Techniques
• Part III: Vectorization Techniques
• Part IV: BFloat16 Kernel Optimization

Chinese version for this chapter, link.

nadavrot

High-Performance Matrix Multiplication

This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).

Intro

Matrix multiplication is a mathematical operation that defines the product of

xianyi

#include <cblas.h>
#include <stdio.h>

void main()
{
  int i=0;
  double A[6] = {1.0,2.0,1.0,-3.0,4.0,-1.0};         
  double B[6] = {1.0,2.0,1.0,-3.0,4.0,-1.0};  
  double C[9] = {.5,.5,.5,.5,.5,.5,.5,.5,.5}; 
  cblas_dgemm(CblasColMajor, CblasNoTrans, CblasTrans,3,3,2,1,A, 3, B, 3,2,C,3);