Article URL: https://mitchellh.com/writing/everyone-should-know-simd Comments URL: https://news.ycombinator.com/item?id=49010648 Points: 83 # Comments: 31

SIMD has a reputation for being complex. I've met many very good software engineers who dismiss it as something too complex to learn or a niche optimization meant for only the highest-performance software, not useful in everyday programming. I think that's wrong. SIMD can be simple to understand1, and common "process N values at a time" SIMD code to speed up a naive for loop almost always follows the same general shape. Once you learn the basics, writing SIMD is just about as easy as a for loop. And when it's not, it's usually a good sign to skip it for now. This post uses Zig for examples but is a general piece that applies to any programming language. Support for SIMD instructions varies by programming language and I hope that more programming languages expose these generic concepts in the future! I hate that I have to do this for every post now, but I also want to note this was completely hand-written with no AI assistance. SIMD allows a CPU to operate on multiple values in parallel. For example, instead of comparing one byte at a time, a CPU can compare 4, 8, or even more bytes with a single instruction. This results in a localized speedup that directly maps to the parallelism: you process data 4x, 8x, or even faster. The only real requirement for this to pay off is that you need to be regularly processing a large enough number of bytes. If you're doing these for loops across data that is only ever a handful or dozens of bytes, it's not worth it. But if this is iterating over hundreds, thousands, millions of bytes, the payoff will be huge. That's the basics. Projects such as simdutf and simdjson take this to an extreme and use SIMD techniques that can be difficult to understand. But you do not need to write algorithms like those to benefit from SIMD. The common case is dramatically simpler.