Revision: 06.08.2023, https://compute.toys/view/407
fn sdSphere(p: vec3f, r: f32) -> f32 {
return length(p) - r;
}
Revision: 06.08.2023, https://compute.toys/view/407
fn sdSphere(p: vec3f, r: f32) -> f32 {
return length(p) - r;
}
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).
Matrix multiplication is a mathematical operation that defines the product of
// MIT License | |
// Copyright (c) 2018 Boris Polania | |
// Permission is hereby granted, free of charge, to any person obtaining a copy | |
// of this software and associated documentation files (the "Software"), to deal | |
// in the Software without restriction, including without limitation the rights | |
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
// copies of the Software, and to permit persons to whom the Software is | |
// furnished to do so, subject to the following conditions: |
#!/bin/sh | |
REPOSRC=$1 | |
LOCALREPO=$2 | |
# We do it this way so that we can abstract if from just git later on | |
LOCALREPO_VC_DIR=$LOCALREPO/.git | |
if [ ! -d $LOCALREPO_VC_DIR ] | |
then |