sse2neon
simdjson
sse2neon | simdjson | |
---|---|---|
7 | 65 | |
1,224 | 18,386 | |
1.2% | 0.5% | |
7.3 | 9.2 | |
16 days ago | 8 days ago | |
C++ | C++ | |
MIT License | Apache License 2.0 |
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sse2neon
- sse2neon - A C/C++ header file that converts Intel SSE intrinsics to Aarch64 NEON intrinsic
- A C/C++ header file that converts Intel SSE intrinsics to Aarch64 NEON intrinsic
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Porting Architecture Specific C/C++ Intrinsics to Graviton
The sse2neon project is a quick way to get C/C++ applications compiling and running on Graviton. The sse2neon header file provides NEON implementations for x64 intrinsics so no source code changes are needed. Each function call (intrinsic) is simply replaced with NEON instructions and will just work on Graviton.
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An AWS Community Builder Story
To continue our collaboration I contributed some small changes to KasmVNC on GitHub to use sse2neon for a performance critical part of the application which uses SSE intrinsics and needed to be changed to NEON intrinsics.
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Deserializing JSON Fast
I think the talk is very clearly laid out as an incremental journey, and each stepping stone involves contextual decision-making. I don't think Andreas is saying "you must end up with the SSE2 implementation at the end". Using machine-specific intrinsics is another dependency decision very similar to deciding to use a given library. I would have loved the talk and probably still thought of it and posted it, even if it ended before the intrinsics (but I think he does an excellent job at that part too).
And porting SSE2 to Neon is actually pretty easy -- if you use https://github.com/DLTcollab/sse2neon, IME it's very easy to do incrementally (or avoid or postpone indefinitely, depending on your needs).
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PortableGL: An MIT licensed implementation of OpenGL 3.x-ish in clean C
I have a private cross-platform port, I’m waiting on the resolution of his latest GitHub issue to submit my changes. sse2neon (https://github.com/DLTcollab/sse2neon) was a big help - I also wrote a very primitive sse2scalar for raspbian builds where neon is unavailable. Honestly SIMD doesn’t help much, as you’re usually memory bound under SWGL. The biggest perf win is any amount of asynchronous execution - running off the main thread is good enough and could be applied to your library externally through a command buffer without any changes to your code.
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Success porting VCV into aarch64 linux! (Usable on Android Devices)
You should go to /include/simd and download sse2neon.h into the folder. Replace appearing in any source files in that directory with "sse2neon.h". You will still encounter errors; remove the lines causing problems, typically containing the phrase ZERO_MODE. ARM processors does not require it.
simdjson
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Tips on adding JSON output to your command line utility. (2021)
It's also supported by simdjson [0] (which has a lot of language bindings [1]):
> Multithreaded processing of gigantic Newline-Delimited JSON (ndjson) and related formats at 3.5 GB/s
[0] https://simdjson.org/
[0] https://github.com/simdjson/simdjson?tab=readme-ov-file#bind...
- 1BRC Merykitty's Magic SWAR: 8 Lines of Code Explained in 3k Words
- Training great LLMs from ground zero in the wilderness as a startup
- simdjson: Parsing Gigabytes of JSON per Second
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Use any web browser as GUI, with Zig in the back end and HTML5 in the front end
String parsing is negligible compared to the speed of the DOM which is glacially slow: https://news.ycombinator.com/item?id=38835920
Come on, people, make an effort to learn how insanely fast computers are, and how insanely inefficient our software is.
String parsing can be done at gigabytes per second: https://github.com/simdjson/simdjson If you think that is the slowest operation in the browser, please find some resources that talk about what is actually happening in the browser?
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Cray-1 performance vs. modern CPUs
Thanks for all the detailed information! That answers a bunch of my questions and the implementation of strlen is nice.
The instruction I was thinking of is pshufb. An example ‘weird’ use can be found for detecting white space in simdjson: https://github.com/simdjson/simdjson/blob/24b44309fb52c3e2c5...
This works as follows:
1. Observe that each ascii whitespace character ends with a different nibble.
2. Make some vector of 16 bytes which has the white space character whose final nibble is the index of the byte, or some other character with a different final nibble from the byte (eg first element is space =0x20, next could be eg 0xff but not 0xf1 as that ends in the same nibble as index)
3. For each block where you want to find white space, compute pcmpeqb(pshufb(whitespace, input), input). The rules of pshufb mean (a) non-ascii (ie bit 7 set) characters go to 0 so will compare false, (b) other characters are replaced with an element of whitespace according to their last nibble so will compare equal only if they are that whitespace character.
I’m not sure how easy it would be to do such tricks with vgather.vv. In particular, the length of the input doesn’t matter (could be longer) but the length of white space must be 16 bytes. I’m not sure how the whole vlen stuff interacts with tricks like this where you (a) require certain fixed lengths and (b) may have different lengths for tables and input vectors. (and indeed there might just be better ways, eg you could imagine an operation with a 256-bit register where you permute some vector of bytes by sign-extending the nth bit of the 256-bit register into the result where the input byte is n).
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Codebases to read
Additionally, if you like low level stuff, check out libfmt (https://github.com/fmtlib/fmt) - not a big project, not difficult to understand. Or something like simdjson (https://github.com/simdjson/simdjson).
- Simdjson: Parsing Gigabytes of JSON per Second
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Building a high performance JSON parser
Everything you said is totally reasonable. I'm a big fan of napkin math and theoretical upper bounds on performance.
simdjson (https://github.com/simdjson/simdjson) claims to fully parse JSON on the order of 3 GB/sec. Which is faster than OP's Go whitespace parsing! These tests are running on different hardware so it's not apples-to-apples.
The phrase "cannot go faster than this" is just begging for a "well ackshully". Which I hate to do. But the fact that there is an existence proof of Problem A running faster in C++ SIMD than OP's Probably B scalar Go is quite interesting and worth calling out imho. But I admit it doesn't change the rest of the post.
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New package : lspce - a simple LSP Client for Emacs
I have same question as /u/JDRiverRun : how do you deal with JSON, do you parse json on Rust side or on Emacs side. I see that you are requiring json.el in your lspce.el, but I haven't looked through entire file carefully. If you parse on Rust side, do you use simdjson (there are at least two Rust bindings to it)? If yes, what are your impressions, experiences compared to more "standard" json library?
What are some alternatives?
yenten-arm-miner-yespowerr16 - ARM 64 CPU miner for Yespower variant algorithms
RapidJSON - A fast JSON parser/generator for C++ with both SAX/DOM style API
KasmVNC - Modern VNC Server and client, web based and secure
jsoniter - jsoniter (json-iterator) is fast and flexible JSON parser available in Java and Go
simde - Implementations of SIMD instruction sets for systems which don't natively support them.
json - JSON for Modern C++
Tow-Boot - An opinionated distribution of U-Boot. — https://matrix.to/#/#Tow-Boot:matrix.org?via=matrix.org
json-schema-validator - JSON schema validator for JSON for Modern C++
libsamplerate - An audio Sample Rate Conversion library
JsonCpp - A C++ library for interacting with JSON.
cglm - 📽 Highly Optimized 2D / 3D Graphics Math (glm) for C
json - A C++11 library for parsing and serializing JSON to and from a DOM container in memory.