# What is SIMD?

By Huon Wilson — Published 10 Jul 2015

## Contents

I’m currently in San Francisco doing an internship at Mozilla Research, working on creating functionality for SIMD in the Rust programming language.

(This post is designed to describe what I’m doing for people not necessarily familiar with programming or SIMD.)

## What is SIMD?

SIMD stands for “Single Instruction, Multiple Data”, and refers to functionality that a lot of computer hardware has for operating on multiple numbers at once. (Essentially 100% of all desktops and laptops and many modern phones have support for it.)

At a high-level, computers only operate on numbers. A program running on the computer will be executing sequences of instructions like

• multiply the result and z,
• store that number to location p,
• repeat (until it’s been done 100 times).

Usually each instruction is a simple operation. If boxes are numbers, the first two steps above (which are run 100 times) might look like:

Each operation is working with just two numbers… but imagine if we could instead do the same operation to many pairs at the same time: things would go faster.

This is exactly what SIMD offers. The operation instead looks like:

If we’re doing 4 things at once, hopefully it is about 4 times faster! (We’d only have to repeat that 25 times to do the whole sequence above.)

Doing arithmetic in parallel is definitely useful, but one of the more interesting parts of SIMD is how it allows doing relatively complicated rearragements of data efficiently. SIMD vectors can be shuffled, swizzled, blended, permuted…

These shuffles allow super-linear speed-ups: even if the computer can only do 4 things at once, shuffles mean some operations can become 5 or more times faster!

The SIMD operations allow a pile of common operations to be performed much faster, allowing software to be snappier, smoother and use less battery.

There are a few common uses for SIMD:

• rendering graphics/text to your screen, which often involves doing the exactly same relatively simple arithmetic operations a lot (your browser is probably using SIMD to display this page).
• decoding compressed pictures, videos and audio, where being faster means using less battery: very important in the age of the laptop/tablet/phone.
• scientific computing will often need to do some heavy-weight number-crunching, and being able to do that four (or eight, or sixteen) times faster can be very nice.

## What does “creating SIMD support” mean?

AKA, what am I doing with my days?

First, an introduction to what “programming” means. A programmer generally spends their time either thinking, or editing text documents: source code. The source code is written by the programmer to describe all the things that the computer needs to do. A program (a compiler) will then convert that source code into the sequence of instructions the computer needs to execute (machine code).

(A compiler is itself a computer program and so has its own source code, which was converted to machine code by a different compiler which also has its own source code, which was converted to machine code by another one… all the way back to the first programs, written directly in machine code by humans: no compiler to help.)

There are a lot of different programming languages in the world: each one has its own compilers that understand source code written in that language, and each of those languages has its own specialties. Some languages are simple and relatively easy to learn at the expense of being slower or less flexible, while others are more complicated but offer more control, flexibility and/or speed. The Rust programming language is relatively new one being created by Mozilla, and fits into the latter category.

Currently, the compiler for Rust doesn’t have good support for generating the SIMD instructions, so part of my work is making modifications to the Rust compiler’s own source code so that it does this better. However, the interface this exposes is very low-level: it has complete control, but requires a lot of effort to use. So part of my project is also building a collection of Rust code (a library) that wraps up the raw functionality into something nicer and easier to use.

Over the past few days I’ve made some big steps. I posted my first design document for initial public feedback, and then a revised form as an official proposal, but I also made some progress with the actual code.

It’s a (rather basic) rendering of the Mandelbrot set, using a sketch of my nicer library.

Somewhat unusually for SIMD, I can run it on many different types of computers without having to change the code at all: that screenshot is when running on my computer, but I can run it on my phone, a little box similar to a Raspberry Pi, and in a variety of emulators… and they all give exactly the same output. (It runs approximately 3× faster than the non-SIMD version.)

It’s a simple example, but it’s a nice first step.

I'm Huon Wilson huon_w, a mathematically and statistically inclined software engineer, currently working on the Swift team at Apple, but interested from hearing from you. Before that I was a long-term volunteer on Rust's core team.

## Latest posts

• ### Myths and Legends about Integer Overflow in Rust

Integer overflow detection/handling in Rust is sometimes misunderstood.
• ### Memory Leaks are Memory Safe

Memory unsafety and memory leaks are distinct concepts, despite their names. Languages that are merely memory safe (both Rust and GC-reliant managed ones) have no guarantee of preventing memory leaks.
• ### Rreverrse Debugging

rr is the debugger for Rust (et al.) that is is almost too good to be true.