| \usepackage{listings} | |
| \usepackage{color} | |
| \definecolor{dkgreen}{rgb}{0,0.6,0} | |
| \definecolor{gray}{rgb}{0.5,0.5,0.5} | |
| \definecolor{mauve}{rgb}{0.58,0,0.82} | |
| \lstset{language=SQL, | |
| basicstyle={\small\ttfamily}, | |
| belowskip=3mm, | |
| breakatwhitespace=true, |
| import matplotlib.pyplot as plt | |
| #for plotting | |
| import numpy as np | |
| # create plot | |
| fig, ax = plt.subplots() | |
| bar_width = 0.15 | |
| opacity = 0.8 | |
| xlabel= np.array([8, 16, 32, 64]) |
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
| # /------------------------------------------\ | |
| # | don't forget to download the .tp file | | |
| # | and place it in the user's directory :› | | |
| # | | | |
| # | also install lolcat: | | |
| # | https://github.com/busyloop/lolcat | | |
| # \------------------------------------------/ | |
| alias test-passed='if [ "$?" -eq "0" ]; then lolcat ~/.tp -a -s 40 -d 2; fi;' |
| use std::str; | |
| fn main() { | |
| // -- FROM: vec of chars -- | |
| let src1: Vec<char> = vec!['j','{','"','i','m','m','y','"','}']; | |
| // to String | |
| let string1: String = src1.iter().collect::<String>(); | |
| // to str | |
| let str1: &str = &src1.iter().collect::<String>(); | |
| // to vec of byte |
