jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

rygorous

#define _CRT_SECURE_NO_DEPRECATE

#include <stdio.h>
#include <string.h>
#include <Windows.h>

// This allocates a "magic ring buffer" that is mapped twice, with the two
// copies being contiguous in (virtual) memory. The advantage of this is
// that this allows any function that expects data to be contiguous in
// memory to read from (or write to) such a buffer. It also means that

kevin-smets

Default

Powerlevel10k

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

MattPD

Program Analysis Resources

(draft; work in progress)

See also:

• Compilers
  • correctness
• Program analysis:
• Dynamic analysis - instrumentation, translation, sanitizers