List of open source projects using SIMD to achieve extreme performance
source link: https://opensourceweekly.org/issues/7/
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Today we are going to talk about high performance. Not the standard distributed cloud blahblah but high performance on a single core on a single machine. Please welcome SIMD instructions.
Did you know?
What are SIMD instructions?
SIMD (for Single Instruction, Multiple Data) are special instructions on CPUs and GPUs that allow them to perform an operation on multiple bytes with only one instruction.
It is often called vectorization because operations are applied to a vector of data with a single instruction.
It allows to implement very fast algorithms on a single thread on general purpose hardware, as opposed to specific hardware acceleration like AES-NI .
It is particularly used in machine learning, cryptography, databases and content processing (video / image / audio encoding) and is a good alternative to multithreading.
MMX, SSE, AVX, AVX-512 are SIMD instructions for Intel. NEON for ARM.
“JSON parser which picks up values directly without performing tokenization in Rust”
faster (MPL 2.0)
“Easy, powerful, portable, absurdly fast numerical calculations. Includes static dispatch with inlining based on your platform and vector types, zero-allocation iteration, vectorized loading/storing, and support for uneven collections." For Rust.
ncnn (BSD 3-Clause)
A high-performance neural network inference framework optimized for the mobile platform by Tencent.
mandel-simd (public domain)
Mandelbrot Set in SSE, AVX, and NEON.
Project of the community
QuestDB (Apache 2.0)
“QuestDB is a NewSQL relational database designed to process time-series data, faster. Our approach comes from low-latency trading. QuestDB’s stack is engineered from scratch, zero-GC Java and dependency-free. The whole database and console fits in a 3.5Mb package." They are using SIMD to achieve extreme performance (see below).
Unfortunately using SIMD is not a silver bullet and may slow down your multithreaded programs due to how some intel’s processors throttle.
With their new 4.2 release, QuestDB (a time-series database) introduced SIMD which made their (already fast) aggregations faster by 100x.
This is the detailed explanation of why and how MinIO ported simdjson to Go.
The difference between SIMD, SIMT and SMT and how it works in Nvidia GPUs.
A good write-up about how to transpose the safe and zero-cost abstraction philosophy of Rust to the SIMD world.
An overview of using SIMD instructions with Go for different processor architectures.
This research paper describes how they achieved base64 encoding and decoding at almost the speed of a
. Really impressive.
A concrete guide of using SIMD to speed up an algorithm in a portable way (in Rust).
This week has been particularly bad regarding security. Major vulnerabilities have been patched in Firefox (2 times!), Ubuntu’s Linux Kernel, Red Hat’s Linux Kernel, Suse’s Linux Kernel, Android, and more.
Go update right now (browsers need to be restarted to apply auto-updates).
Stay safe :v:
Aggregate valuable and interesting links.
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