simdutf
simde
simdutf | simde | |
---|---|---|
11 | 7 | |
960 | 2,171 | |
4.4% | 1.5% | |
9.1 | 9.1 | |
3 days ago | 9 days ago | |
C++ | C | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
simdutf
- Glibc Buffer Overflow in Iconv
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Vectorizing Unicode conversions on real RISC-V hardware
The project was mostly inspired by simdutf [0] which has been around for a couple of years already, and I don't think iconv has any of its vectorized implementations for other architectures.
[0] https://github.com/simdutf/simdutf
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Cray-1 performance vs. modern CPUs
I'm actually doing something quite similar in my, in progress, unicode conversion routines.
For utf8 validation there is a clever algorithm that uses three 4-bit look-ups to detect utf8 errors: https://github.com/simdutf/simdutf/blob/master/src/icelake/i...
Aside on LMUL, if you haven't encountered it yet: rvv allows you to group vector registers when configuring the vector configuration with vsetvl such that vector instruction operate on multiple vector registers at once. That is, with LMUL=1 you have v0,v1...v31. With LMUL=2 you effectively have v0,v2,...v30, where each vector register is twice as large. with LMUL=4 v0,v4,...v28, with LMUL=8 v0,v8,...v24.
In my code, I happen to read the data with LMUL=2. The trivial implementation would just call vrgather.vv with LMUL=2, but since we only need a lookup table with 128 bits, LMUL=1 would be enough to store the lookup table (V requires a minimum VLEN of 128 bits).
So instead I do six LMUL=1 vrgather.vv's instead of three LMUL=2 vrgather.vv's because there is no lane crossing required and this will run faster in hardware: (see [0] for a relevant mico benchmark)
# codegen for equivalent of that function
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What C++ library do you wish existed but hasn’t been created yet?
utf8 normalization, stemming, case insensitive comparison. https://github.com/unicode-rs example for rust What are options for C++? 1. translate to utf16 ( https://github.com/simdutf/simdutf ) and use icu -- slow 2. boost text, https://github.com/tzlaine/text , also slow (because the author doesn't care or couldn't care), we made a lot of patches to make our library faster than lucene, but still this part is slower than icu for utf16 (icu for utf16 also very slow...)
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[Preprint] Transcoding Unicode Characters with AVX-512 Instructions
You can find the corresponding assembly code in this repository. The main branch only contains implementations based on C++ with intrinsics.
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What's everyone working on this week (10/2023)?
The next big thing is making it LSP-compatible. All language servers must implement UTF-16 based character offsets, which is kinda unfortunate considering that files are much more likely to be stored in UTF-8 (I think?). I don't want to do the UTF-8 -> UTF-16 transcoding, so instead I'll use the excellent simdutf library to count how much code points a UTF-8 string would take if it was transcoded into UTF-16 — which is much faster than actual transcoding. So this is what I'm going to do this week — rewriting parsers to produce UTF-16 offsets + some final benchmarking. After that is done, I'll consider the "research" part of this project completed and will start writing an actual Markdown parser.
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Why would a language not natively support SIMD?
You can find the assembly code here: https://github.com/simdutf/simdutf/tree/clausecker The corresponding C++ code is in the main branch.
- High speed Unicode routines using SIMD
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text-2.0-rc1 with UTF8 underlying representation is available for testing!
Or via an ultrafast simdutf.
- Simdutf: Unicode validation and transcoding at billions of characters per second
simde
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The Case of the Missing SIMD Code
I was curious about these libraries a few weeks ago and did some searching. Is there one that's got a clearly dominating set of users or contributors?
I don't know what a good way to compare these might be, other than perhaps activity/contributor count.
[1] https://github.com/simd-everywhere/simde
[2] https://github.com/ermig1979/Simd
[3] https://github.com/google/highway
[4] https://gitlab.com/libeigen/eigen
[5] https://github.com/shibatch/sleef
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Rise: Accelerate the Development of Open Source Software for RISC-V
I note that SIMDe doesn't have RISC-V support yet (but it does support Loongson LoongArch):
https://github.com/simd-everywhere/simde/
There are still a ton of things to do to get the Debian riscv64 port going too:
https://wiki.debian.org/PortsDocs/New
- SIMD intrinsics and the possibility of a standard library solution
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Portable SIMD library
SIMDe is everything you're after: https://github.com/simd-everywhere/simde
- SIMD Everywhere – SIMD intrinsics on hardware which doesn't support them
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Making Your Own Tools
> low level code that can run on multiple hardware architectures
I thought SIMD Everywhere was a pretty interesting project for that, lets you write x86 SSE/AVX code and run it on non-x86 architectures:
https://github.com/simd-everywhere/simde
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Adobe Photoshop Ships on Macs Apple Silicon/M1 – 50% Faster
> architecture-specific features such as SSE/AVX which is not portable.
I don’t have hands-on experience, but somewhere on HN I saw this: https://github.com/simd-everywhere/simde If starting a new cross-platform project today, I would try that library first, before doing the usual intrinsics.
What are some alternatives?
simdutf8 - SIMD-accelerated UTF-8 validation for Rust.
nsimd - Agenium Scale vectorization library for CPUs and GPUs
DirectXMath - DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
sse2neon - A translator from Intel SSE intrinsics to Arm/Aarch64 NEON implementation
eve - Expressive Vector Engine - SIMD in C++ Goes Brrrr
android-inline-hook - :fire: ShadowHook is an Android inline hook library which supports thumb, arm32 and arm64.
Vc - SIMD Vector Classes for C++
libsimdpp - Portable header-only C++ low level SIMD library
simdjson - Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
Sparkle - A software update framework for macOS
colrcv - C Library for converting Colours between different Colour Models
picoRTOS - Very small, lightning fast, yet portable RTOS with SMP suppport