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

jFransham

Achieving warp speed with Rust

Contents:

• Number one optimization tip: don't
• Never optimize blindly
• Don't bother optimizing one-time costs
• Improve your algorithms
• CPU architecture primer
• Keep as much as possible in cache
• Keep as much as possible in registers

agnes1

package org.treeml;

import java.io.IOException;
import java.util.*;
import java.util.logging.Logger;

/**
 * Evaluates that a document (the referrer) makes references existing values in another document
 * or group of documents (the source).
 * Created by Ags on 6/25/2016.

KdotJPG

/**
 * K.jpg's OpenSimplex 2, smooth variant ("SuperSimplex")
 *
 * More language ports, as well as legacy 2014 OpenSimplex, can be found here:
 * https://github.com/KdotJPG/OpenSimplex2
 */

public class OpenSimplex2S {

    private static final long PRIME_X = 0x5205402B9270C86FL;

pklaus

#undef HID_ENABLED

// Arduino Due ADC->DMA->USB 1MSPS
// by stimmer
// from http://forum.arduino.cc/index.php?topic=137635.msg1136315#msg1136315
// Input: Analog in A0
// Output: Raw stream of uint16_t in range 0-4095 on Native USB Serial/ACM

// on linux, to stop the OS cooking your data: 
// stty -F /dev/ttyACM0 raw -iexten -echo -echoe -echok -echoctl -echoke -onlcr