simdutf
Magic Enum C++
simdutf | Magic Enum C++ | |
---|---|---|
11 | 44 | |
960 | 4,424 | |
4.8% | - | |
9.1 | 8.1 | |
3 days ago | 3 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
-
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
-
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
-
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...)
-
[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.
-
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.
-
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
-
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
Magic Enum C++
-
What C++ library do you wish existed but hasn’t been created yet?
I'm not sure this is quite what you're asking for, but this library has been super helpful to me in the past : https://github.com/Neargye/magic_enum
- Usable Magic Enums for C++
-
Fully Permissive License C++ Logger For Embedded System
Also, a shoutout to Magic Enum: https://github.com/Neargye/magic_enum
- Favorite Ways of Stringifying Enums
-
enum_name (yet another enum to/from string conversion utility >=C++11)
What does this have to offer over magic_enum?
-
quill v2.7.0 released - Asynchronous Low Latency C++ Logging Library
But it's a hack, and I prefer not to use hacks in production, because of their significant limitations:
-
Enums print numbers instead of words
You can either write a to string(view) function for your enum or use https://github.com/Neargye/magic_enum
-
Enums with methods
Why reinvent the wheel? magic_enum
-
Error: Boost bimap can't convert const CompatibleKey to Key&
Also if you want to convert enum members to string representation I suggest you just use magic_enum instead, much smaller dependency.
-
Macro to write enum and converter from and to string
Magic Enum provides that.
What are some alternatives?
simdutf8 - SIMD-accelerated UTF-8 validation for Rust.
Nameof C++ - Nameof operator for modern C++, simply obtain the name of a variable, type, function, macro, and enum
DirectXMath - DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
Protobuf - Protocol Buffers - Google's data interchange format
simde - Implementations of SIMD instruction sets for systems which don't natively support them.
cereal - A C++11 library for serialization
eve - Expressive Vector Engine - SIMD in C++ Goes Brrrr
FlatBuffers - FlatBuffers: Memory Efficient Serialization Library
Vc - SIMD Vector Classes for C++
Boost.Serialization - Boost.org serialization module
simdjson - Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
pfr - std::tuple like methods for user defined types without any macro or boilerplate code