simd_decimal
vectorized decimal parsing (by vgatherps)
version2
Vector class library, latest version (by vectorclass)
| simd_decimal | version2 | |
|---|---|---|
| 1 | 6 | |
| 10 | 1,220 | |
| - | 1.6% | |
| 10.0 | 5.8 | |
| over 1 year ago | 3 months ago | |
| Rust | C++ | |
| MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
simd_decimal
Posts with mentions or reviews of simd_decimal.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-08.
-
SIMD intrinsics and the possibility of a standard library solution
Compare this neon parser and this sse parser, or for a very direct example what happens if you naively do the x86 method of vector search on arm. The shuffle and accumulation for each parser is drastically different, since the set of horizontal multiply-accumulates are different.
version2
Posts with mentions or reviews of version2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-08.
-
SIMD intrinsics and the possibility of a standard library solution
Vector class library - 938 GH stars
- Checking for the absence of a string, naive AVX-512 edition
-
-🎄- 2022 Day 4 Solutions -🎄-
Most of the time is spent parsing, but this problem lends itself nicely to a SIMD formulation, which using vectorclass doesn't even require detailed knowledge of the intrinsics. Hot runs take ~14 µs on a Core i9-12900K, including I/O. Full code is (here)[https://github.com/ahans/aoc2022/blob/main/cpp/day04.cc], the interesting part is this, where we process 32 elements at once:
- Significantly faster quicksort using SIMD
- Parsing JSON faster with Intel AVX-512
- What do you think is faster for batch-processing a lot of "double-type" arithmetic?
What are some alternatives?
When comparing simd_decimal and version2 you can also consider the following projects:
ispc - Intel® Implicit SPMD Program Compiler
highway - Performance-portable, length-agnostic SIMD with runtime dispatch
sleef - SIMD Library for Evaluating Elementary Functions, vectorized libm and DFT
aoc22 - Advent of Code solutions for 2022 (in Python)
simde - Implementations of SIMD instruction sets for systems which don't natively support them.
advent2022
xsimd - C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, AVX512, NEON, SVE))
adventOfCode2022
Skia - Skia is a complete 2D graphic library for drawing Text, Geometries, and Images.
Day4 - My (messy) Python3 solution for day4's puzzle.