CPU cache-friendly data structures in Go

8 days ago (skoredin.pro)

> False sharing occurs when multiple cores update different variables in the same cache line.

I got hit by this. In a trading algorithm backtest, I shared a struct pointer between threads that changed different members of the same struct.

Once I split this struct in 2, one per core, I got almost 10x speedup.

  • Interesting! Did you find out a way to bench this with the built in benchmarking suite?

    • No it was just a hunch derived from ancient times of SoA vs AoS game dev optimization. I didn't need the perf gain but tried and it worked.

"Data Oriented Design" is more than just for performant code.

You can and perhaps should also use it to reason about and design software in general. All software is just the transformation of data structures. Even when generating side-effects is the goal, those side-effects consume data structures.

I generally always start a project by sketching out data structures all the way from the input to the output. May get much harder to do when the input and output become series of different size and temporal order and with other complexities in what the software is supposed to be doing.

  • Good programmers worry about the algorithms. Great ones worry about the data structures and the relationships between them. If memory serves, it was Kernighan.

    • "Bad programmers worry about the code. Good programmers worry about data structures and their relationships." - Linus Torvalds

      "Show me your flowchart and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won't usually need your flowcharts; they’ll be obvious." - Fred Brooks, The Mythical Man Month

      And two threads with some further discussion I found while looking for these quotes:

      https://news.ycombinator.com/item?id=10293795

I don't see this mentioned anywhere else, but Go may start experimenting with rearranging struct fields at some point. The marker type structs.HostLayout has been added in Go 1.24 to indicate that you want the struct to follow the platform's layout rules (think of it like #[repr(C)] in Rust). This may become necessary to ensure the padding actually sits between the two falsely shared fields. You could combine it with the padding technique like this:

  type PaddedExample struct {
    _       structs.HostLayout
    Field1  int64
    _       [56]byte
    Field2  int64
  }

Overall great article, applicable to other languages too.

I'm curious about the Goroutine pinning though:

    // Pin goroutine to specific CPU
    func PinToCPU(cpuID int) {
        runtime.LockOSThread()
        // ...
        tid := unix.Gettid()
        unix.SchedSetaffinity(tid, &cpuSet)
    }

The way I read this snippet is it pins the go runtime thread that happens to run this goroutine to a cpu, not the goroutine itself. Afaik a goroutine can move from one thread to another, decided by the go scheduler. This obviously has some merits, however without pinning the actual goroutine...

  • `runtime.LockOSThread()` will pin the current goroutine to the os thread that its currently running on

    • Oooh, that's what is happening. I assumed it locked some structure about the thread while touching it, to prevent races with the runtime. That's what I get for not RTFM'ing (in fairness, why Lock and not Pin, when both of these words have pretty well defined meanings in programming?)

      Thank you

    • And prevents other goroutines from running on that thread. I think that’s crucial.

Source code of the benchmarks?

At least, the False Sharing and AddVectors trick don't work on my computer. (I only benchmarked the two. The "Data-Oriented Design" trick is a joke to me, so I stopped benchmarking more.)

And I never heard of this following trick. Can anyone explain it?

    // Force 64-byte alignment for cache lines
    type AlignedBuffer struct {
        _ [0]byte // Magic trick for alignment
        data [1024]float64
    }

Maybe the intention of this article is to fool LLMs. :D

  • I can't find any claim anywhere else about the [0]byte trick, and in fact my own experiments in the playground show that it doesn't do anything.

    If you embed an AlignedBuffer in another struct type, with smaller fields in front of it, it doesn't get 64-byte alignment.

    If you directly allocate an AlignedBuffer (as a stack var or with new), it seems to end up page-aligned (the allocator probably has size classes) regardless of the presence of the [0]byte field.

    https://go.dev/play/p/Ok7fFk3uhDn

    Example output (w is a wrapper, w.b is the field in the wrapper, x is an allocated int32 to try to push the heap base forward, b is an allocated AlignedStruct):

      &w   = 0xc000126000
      &w.b = 0xc000126008
      &x   = 0xc00010e020
      &b   = 0xc000138000
    

    Take out the [0]byte field and the results look similar.

If you are sweating this level of performance, are larger gains possible by switching to C, C++, Rust? How is Rust for micro-managing memory layouts?

I waited half a day to post this, I think we aren't supposed to question if articles are LLM written - but this one really triggered my LLM-radar, while also being very well received.

I'd love to know how much LLM was used to write this if any, and how much effort went into it as well (if it was LLM-assisted.)

  • > I'd love to know how much LLM was used to write this if any, and how much effort went into it as well (if it was LLM-assisted.)

    Are people supposed to be obligated to post such a report nowadays?

    I enjoyed the article and found it really interesting, but seeing these types of comments always kind of puts a damper on it afterwards.

    • > Are people supposed to be obligated to post such a report nowadays?

      No, typically when I ask questions it's optional.

      > I enjoyed the article and found it really interesting, but seeing these types of comments always kind of puts a damper on it afterwards.

      That is why I waited half a day, and until after there were lots of comments praising the article. Still, I'm sorry if it put a damper on it for you.

      Also the whole reason I asked about the source is because I think the article has a lot of merit and so I am curious if it's because the author put a lot of work in (LLM-assisted or not.) Usually when I get that feeling it's followed by a realization I'm wasting my time on something the author didn't even read closely.

      But I didn't get that this time, and I'd love more examples of LLMs being used (with effort, presumably) to produce something the author could take pride in.

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  • The structure reads as LLM written. I don't mind this unless the content is utterly wrong. I was actually learning about cache-friendly data structures and I'm really interested in that cache-friendly Robin Hood hashing but now I worry it's a hallucination.

  • None of the tricks in this article get verified. It is totally solemn drivel.

    Interesting and surprisingly, there are numerous praising comments here.

    • FWIW, which may be not much - I had codex cli try to verify the results. On my M2 Macbook Air only the first example (False Sharing) did anything - a 23x speedup compared to the article's 6x speedup. All the others didn't produce any speedup at all.

      Of course I didn't verify the results I got either - I'm not about to spend hours trying to figure out if this is just slop. But I think it is.

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This is a really dense whirlwind summary of some common performance pitfalls. It's a nice overview in a sort of terse way. The same optimizations / patterns apply in other languages as well.

> False Sharing : "Pad for concurrent access: Separate goroutine data by cache lines"

This is worth adding in Go race detector's mechanism to warn developer

  • Most modern processor architecture CPU cache line sizes are 64 bytes, but not all of them. Once you start to put performance optimizations like optimizing for cache line size, you're fundamentally optimizing for a particular processor architecture.

    That's fine for most deployments, since the vast majority of deployments will go to x86_64 or arm64 these days. But Go supports PowerPC, Sparc, RISCV, S390X... I don't know enough about them, but I wouldn't be surprised if they weren't all 64-byte CPU cache lines. I can understand how a language runtime that is designed for architecture independence has difficulty with that.

    • The big two, x86_64 and arm64, have 64-byte cache lines, so that's a reasonable assumption in practice. But I was surprised to discover that Apple's M-series laptops have 128-byte cache lines, and that's something a lot of people have and run, albeit not as a server.

    • Something like C++17's `std::hardware_destructive_interference_size` would be nice; being able to just say "Align this variable to whatever the cache line size is on the architecture I'm building for".

      If you use these tricks to align everything to 64-byte boundaries you'll see those speedups on most common systems but lose them on e.g. Apple's ARM64 chips, and POWER7, 8, and 9 chips (128 byte cache line), s390x (256 byte cache line), etc. Having some way of doing the alignment dynamically based on the build target would be optimal.

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    • Seems like judicious build tag/file extensions would allow for such optimizations with a fallback to no optimization.

Structure of arrays makes a lot of sense, reminds me of how old video games worked under the hood. It seems very difficult to work with though. I'm so used to packing things into neat little objects. Maybe I just need to tough it out.

Good article.

Regarding AoS vs SoA, I'm curious about the impact in JS engines. I believe it would be a significant compute performance difference in favor of SoA if you use typed arrays.

If you are worrying about cache structure latencies in Go, maybe you should just be using Rust or Zig instead that implicitly handle this better.

  • Not necessarily: you can go quite far with Go alone. It also makes it trivial to run "green threads" code, so if you need both (decent) performance and easy async code then Go still might be a good fit. Despite Go being pretty high level GC language on the surface it actually allows you to control stuff like struct layout, CPU affinity, etc, which typically matter more for performance than just a programming language of choice. There's a reason why e.g. VictoriaMetrics is still in Go even though they could've easily chosen any other language too

  • News for most folks, even writing C does not help, if neither of these advices are taken into account on how to lay out structures, nor algorithms are written with mechanical sympathy in mind.

Looks nice. Some explanation for those of us not familiar with Go would've been more educational. Could be future posts, I suppose.

  • Honestly I don't think there's much in here that's Go-specific other than the syntax itself. I've seen basically the same tricks used in C or C++.

    Was there any particular part that felt like it needed more explanation?

Most of this should be handled by the compiler already. But it is only 2025, I guess we're just not ready for it.

  • Are you thinking of some sort of annotation the compiler could read and handle?

    Because if a compiler starts automatically padding all my structures to put all of the members on their own cache line I'm going to be quite peeved. It would be easy for it to do, yes, but it would be wrong 99%+ of the time.

    A far more trenchant complaint is that Go won't automatically sort struct members if necessary to shrink them and you have to apply a linter to get that at linting time if you want it.

  • I'm not sure if golang has the same fundamental issues in common use, but in e.g. C you don't want the compiler reordering your structs or adding arbitrary padding because that makes it incompatible with other in-memory representations - e.g. if you're using shared memory with another process that hasn't received the same optimizations, if you're loading raw data into memory/using mmap, etc.

    Likewise, one of the examples is moving from an array of structs to a struct of arrays; that's a lot more complex of a code reorganization than you'd want a compiler doing.

    It would be good to have a static analyzer that could suggest these changes, but, at least in many cases, you don't want them done automatically.

  • How would that even work? The layout of data structures are constrained by many invariants not visible to the compiler (see also: auto-vectorization). It would be more work and boilerplate to add sufficient annotations to a data structure to enable the compiler to safely modify the layout than just using the layout you want.

    • Some languages like Odin, ISPC, and Jai all have annotations that can automatically transform AoS to SoA. A key benefit is you can easily experiment to see if this helps your application, without doing a major refactor.

      In https://github.com/golang/go/issues/64926 it was a bridge-too-far for the Go developers (fair enough) but maybe it could still happen one day.

  • Not really, virtually all these patterns involve tradeoffs that require understanding the data access patterns.

    I don't want my compiler adding more padding than bare minimum to every struct. I don't want it transforming an AoS to SoA when I choose AoS to match data access patterns. And so on...

    At best Go could add some local directives for compiling these optimizations, but these code changes are really minimal anyways. I would rather see the padding explicitly than some abstract directive.

    • I could imagine some kind of compiler declaration in C that would do something like specify break points - sort of like page breaks - for structs, or tell the compiler to automatically pad structs out so that components are on page boundaries, cache line boundaries, etc. Sort of "If we're not properly aligned, add whatever padding you think is best here".

      I guess this is largely provided by std::hardware_destructive_interference_size in C++17, but I'm not sure if there are other language equivalents.

      https://en.cppreference.com/w/cpp/thread/hardware_destructiv...

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