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
$ uname -r
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| Setting up a modern C++ development environment on Linux with Clang and Emacs | |
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Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.
$ python -m SimpleHTTPServer 8000
| $stack, $draws = [], {} | |
| def method_missing *args | |
| return if args[0][/^to_/] | |
| $stack << args.map { |a| a or $stack.pop } | |
| $draws[$stack.pop(2)[0][0]] = args[1] if args[0] == :< | |
| end | |
| class Array | |
| def +@ |
Locate the section for your github remote in the .git/config file. It looks like this:
[remote "origin"]
fetch = +refs/heads/*:refs/remotes/origin/*
url = git@github.com:joyent/node.git
Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this: