xxHash VS libuv

> GPU Hash Table?

How bad would performance have suffered if you sha256'd the lines to build the map? I'm going to guess "badly"?

Maybe something like this in CUDA: https://github.com/Cyan4973/xxHash ?

Examples of fast, simple hashes that are independent enough includes murmur, xxHash, Fowler–Noll–Vo hash function and many others

If you're only using the hash for non-cryptographic applications, there are much faster hashes: https://github.com/Cyan4973/xxHash

I found the benchmark result of AMD ryzen 5950X

But what's the catch, you're thinking ? Well, it is a bit slower than its counterparts when it comes to deserializing (and marginally faster for serializing). To achieve smaller footprint, it uses a few tricks and notably a custom hash table to deduplicate strings. This comes at a cost of course (even when featuring xxHash to speed things up), but keeps the slowdown reasonable (I think).

Non cryptographic hashes has collisions, for example, assume you having content like "abcdefg" which hashed value is "123", in case of weak hash algorithm some other content like "abcdefZ" can also have a hash "123" which basically means such hash function is failed to be unique fingerprint of particular content. BLAKE3 for example can do 6-7Gb/s which make it pretty fast and secure. If your requirement accepts collision with defined error rate, I would advise you to take a look at XXH3 if you need very snappy hash algorithm, which can run at pace or RAM access (30GB/s+), but again, run tests at particular equipment you targeting, may be AES hardware accelerated MeowHash will serve you better.

I wound up on a different team with pre-existing Python code so temporarily shelved my use of Go for a bit, and we used Sanic (an async Python framework built on top of the excellent uvloop & libuv that also powers Node.js) to build some APIs for live channel management & operations. We hand-wrote our OpenAPI and used it to generate documentation and a CLI, which was an improvement over what was there (or not) before. Other teams used the OpenAPI document to generate SDKs to interact with our service.

In the source code of the Node.js opensource project, lib folder contains JavaScript code, mostly wrappers over C++ and function definitions. On the contrary, src folder contains C++ implementations of the functions, which pulls dependencies from the V8 project, the libuv project, the zlib project, the llhttp project, and many more - which are all placed at the deps folder.

Libuv, the C library that gives Node.js its asynchronous, non-blocking I/O capability is responsible for managing the thread pool. Node.js gives you the capability of using additional threads for computationally expensive and long-lasting operations to avoid blocking the event loop.

Node.js is written in C, C++, and JavaScript. The core components of Node.js - the V8 engine and the libuv library - are written in C++ and C, respectively, since these languages provide low-level access to system resources, making them well-suited for building high-performance and efficient applications. JavaScript is mainly used to write the application logic.

x8 apparently https://github.com/libuv/libuv/pull/3952

Notably upgrades to libuv 1.45 which has io_uring support. Faster file system access! Awhh yeah, it's on.

Remarkable what a mild & unintrusive PR adding io_uring was. https://github.com/libuv/libuv/pull/3952

Well, the single-threaded nature ultimately leads to its biggest downfall. Node.js utilizes a synchronous event loop engineered using Libuv that takes in code from the call stack and executes it.