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
| /* @flow */ | |
| import * as I from "immutable"; | |
| /** | |
| * Define an immutable record intended for holding reducer state | |
| * @param spec - the keys and their default values | |
| * @return a state record factory function | |
| */ | |
| export function defineRecord<T: Object>( |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!
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