4 ms·

… except for byte-level processing, variable-length codecs, or mixed-precision numerics. That never works with autovectorization and can’t be solved with genera

… except for byte-level processing, variable-length codecs, or mixed-precision numerics. That never works with autovectorization and can’t be solved with general-purpose SIMD wrappers. For me the solution was to implement those manually, and even at a scale of just 2 libraries I’ve eneded up with somewhat different project layouts & dispatch mechanisms: https://github.com/ashvardanian/SimSIMD https://github.com/ashvardanian/SimSIMD , https://github.com/ashvardanian/StringZilla https://github.com/ashvardanian/StringZilla One big family not covered there, is sparse data-strictures and related algorithms. I’ve only started integrating scatter/gather in AVX-512 and SVE, and on synthetic benchmarks both look promising: https://github.com/ashvardanian/less_slow.cpp/releases/tag/v0.3.0 https://github.com/ashvardanian/less_slow.cpp/releases/tag/v... Those should probably unlock a much wider set of applications for SIMD, but designing libraries for those may benefit from yet another project structure.

dzaima 2y ago
Ah yeah, gather/scatter are indeed a rather problematic thing for autovectorization. That said, with no-alias info (which Rust has a lot of) it's possible: https://rust.godbolt.org/z/zTfo9nxhd https://rust.godbolt.org/z/zTfo9nxhd. Unfortunately it doesn't get autovectorized without the unsafes, but theoretically it should be possible-ish for bounds checking to be autovectorized (most problematic aspect being that it might be hard to annoying-to-impossible to ensure that in the case of multiple panic/UB sources the proper one happens first). I'd imagine in any non-trivial situation you'd want a custom layer of abstractions over whatever the language provides for all languages. For that a portable-simd thing is actually a rather good base, on which you could add custom arch-specific abstractions/ops as desired. Not sure what's problematic with mixed-precision (I know SVE is rather weird for mixed-width elements, but that's about it?), though I primarily don't care about float stuff generally. Also no clue what's problematic with byte-level stuff. Indeed there are still a bunch of things that you want proper manual SIMD for (hell the SIMDful project I work on has an entire DSL for doing nice SIMD), but autovectorization still covers a good amount.
janwas 2y ago
> except for byte-level processing, variable-length codecs, or mixed-precision numerics. That never works with autovectorization and can’t be solved with general-purpose SIMD wrappers. Counterexamples: Chromium's byte-level HTML scanning, several var-len bit packing codecs, and Gemma.cpp's matmul is mixed-precision (fp8->bf16->fp32->fp64). All written with the Highway general-purpose SIMD wrapper. Please revise your post or expand upon the structure/dispatch concern.
- ashvardanian 2y ago
  Interesting references! I remember that Gemma.cpp used Highway, but I haven't checked the others much. Here is a puzzle, then. Let's say we are checking a single register of bytes for element-wise equality with another register of the same size. In AVX2, the output is another YMM register of 0xFF or 0x00 values. In AVX-512, for full ZMM-wide comparisons, it's a 64-bit mask in the K register. I struggle to see a good way to abstract such things, even for two consecutive SIMD generations on x86.
  - dzaima 2y ago
    A simple enough abstraction is to have the mask type have inputs of both element size and count; so for a ≤256-bit product of those you do the homogeneous-bit elements, and for 512-bit you do the packed-bit values. Conversion methods on the mask can convert those to either an explicit full vector, or a packed bit integer, as you need. (and clang can optimize out unnecessary conversions between the two)
    - ashvardanian 2y ago
      Sure, that would make sense, but in AVX-512, there is also a comparison variant for 2x256-bit inputs that outputs a 32-bit mask and another one for 2x128 inputs and a 16-bit output mask. I would use those in different ways, occasionally mixing with the old AVX2 variant, depending on what I’m doing. I have tried to create a generalizable SIMD framework several times in the past, mostly in 2015-17, and still don’t have a good abstraction even between AVX2 and AVX-512.
burntsushi 2y ago
You started with this... take: > Rust feels like a Python developer’s idea of a high-performance computing language. It’s a great language for many kinds of applications — just not when you need to squeeze out every bit of performance from advanced hardware. And went on to say that Rust in particular is problematic for: > byte-level processing It's particularly odd for you to say this given that the memchr Rust crate is just as fast as stringzilla for substring search. And is generally faster in cases where the needle is invariant, because stringzilla doesn't have APIs for amortizing searcher construction. We've had a discussion about this before where I provided receipts[1] and we have not had a meeting of the minds on this point. The thing I'm trying to achieve here is to point out that your claims are contested and there is evidence that you're wrong. And so I'd caution readers to also in turn question your higher level claims about Rust being a "Python developer's idea of a high-performance computing language." [1]: https://old.reddit.com/r/rust/comments/1ayngf6/memchr_vs_stringzilla_benchmarks_up_to_7x/krwqhhb/ https://old.reddit.com/r/rust/comments/1ayngf6/memchr_vs_str...
- ashvardanian 2y ago
  Hey! I just mean that there is a very large category of developers, generally coming from the Python world, expecting that switching to Rust is supposed to solve every performance-oriented problem, providing a State-of-the-Art solution magically :) Sadly, programming doesn't seem to work that way. There are always tradeoffs. Rust does some things very well, but it wouldn't be my first choice for others. MemChr is a lovely package, and there are a few other really cool SIMD projects in the Rust ecosystem. Regardless, my development velocity for HPC-related projects is higher in C/C++, and I get much more flexibility to leverage newer hardware features, like AMX and SME.
- almostgotcaught 2y ago
  Don't worry his comment is obvious clickbait (complete with a plug for a random blogpost written by him). People that matter (people that are actually writing simd for their day job) can immediately spot a poseur (especially relative to you and Raph).
  - 2y ago

dzaima 2y ago

Ah yeah, gather/scatter are indeed a rather problematic thing for autovectorization. That said, with no-alias info (which Rust has a lot of) it's possible: https://rust.godbolt.org/z/zTfo9nxhd https://rust.godbolt.org/z/zTfo9nxhd. Unfortunately it doesn't get autovectorized without the unsafes, but theoretically it should be possible-ish for bounds checking to be autovectorized (most problematic aspect being that it might be hard to annoying-to-impossible to ensure that in the case of multiple panic/UB sources the proper one happens first). I'd imagine in any non-trivial situation you'd want a custom layer of abstractions over whatever the language provides for all languages. For that a portable-simd thing is actually a rather good base, on which you could add custom arch-specific abstractions/ops as desired. Not sure what's problematic with mixed-precision (I know SVE is rather weird for mixed-width elements, but that's about it?), though I primarily don't care about float stuff generally. Also no clue what's problematic with byte-level stuff. Indeed there are still a bunch of things that you want proper manual SIMD for (hell the SIMDful project I work on has an entire DSL for doing nice SIMD), but autovectorization still covers a good amount.

janwas 2y ago

> except for byte-level processing, variable-length codecs, or mixed-precision numerics. That never works with autovectorization and can’t be solved with general-purpose SIMD wrappers. Counterexamples: Chromium's byte-level HTML scanning, several var-len bit packing codecs, and Gemma.cpp's matmul is mixed-precision (fp8->bf16->fp32->fp64). All written with the Highway general-purpose SIMD wrapper. Please revise your post or expand upon the structure/dispatch concern.

ashvardanian 2y ago
Interesting references! I remember that Gemma.cpp used Highway, but I haven't checked the others much. Here is a puzzle, then. Let's say we are checking a single register of bytes for element-wise equality with another register of the same size. In AVX2, the output is another YMM register of 0xFF or 0x00 values. In AVX-512, for full ZMM-wide comparisons, it's a 64-bit mask in the K register. I struggle to see a good way to abstract such things, even for two consecutive SIMD generations on x86.
- dzaima 2y ago
  A simple enough abstraction is to have the mask type have inputs of both element size and count; so for a ≤256-bit product of those you do the homogeneous-bit elements, and for 512-bit you do the packed-bit values. Conversion methods on the mask can convert those to either an explicit full vector, or a packed bit integer, as you need. (and clang can optimize out unnecessary conversions between the two)
  - ashvardanian 2y ago
    Sure, that would make sense, but in AVX-512, there is also a comparison variant for 2x256-bit inputs that outputs a 32-bit mask and another one for 2x128 inputs and a 16-bit output mask. I would use those in different ways, occasionally mixing with the old AVX2 variant, depending on what I’m doing. I have tried to create a generalizable SIMD framework several times in the past, mostly in 2015-17, and still don’t have a good abstraction even between AVX2 and AVX-512.

burntsushi 2y ago

You started with this... take: > Rust feels like a Python developer’s idea of a high-performance computing language. It’s a great language for many kinds of applications — just not when you need to squeeze out every bit of performance from advanced hardware. And went on to say that Rust in particular is problematic for: > byte-level processing It's particularly odd for you to say this given that the memchr Rust crate is just as fast as stringzilla for substring search. And is generally faster in cases where the needle is invariant, because stringzilla doesn't have APIs for amortizing searcher construction. We've had a discussion about this before where I provided receipts[1] and we have not had a meeting of the minds on this point. The thing I'm trying to achieve here is to point out that your claims are contested and there is evidence that you're wrong. And so I'd caution readers to also in turn question your higher level claims about Rust being a "Python developer's idea of a high-performance computing language." [1]: https://old.reddit.com/r/rust/comments/1ayngf6/memchr_vs_stringzilla_benchmarks_up_to_7x/krwqhhb/ https://old.reddit.com/r/rust/comments/1ayngf6/memchr_vs_str...

ashvardanian 2y ago
Hey! I just mean that there is a very large category of developers, generally coming from the Python world, expecting that switching to Rust is supposed to solve every performance-oriented problem, providing a State-of-the-Art solution magically :) Sadly, programming doesn't seem to work that way. There are always tradeoffs. Rust does some things very well, but it wouldn't be my first choice for others. MemChr is a lovely package, and there are a few other really cool SIMD projects in the Rust ecosystem. Regardless, my development velocity for HPC-related projects is higher in C/C++, and I get much more flexibility to leverage newer hardware features, like AMX and SME.
almostgotcaught 2y ago
Don't worry his comment is obvious clickbait (complete with a plug for a random blogpost written by him). People that matter (people that are actually writing simd for their day job) can immediately spot a poseur (especially relative to you and Raph).
- 2y ago