clace VS xxHash

An approach like https://github.com/benbjohnson/hashfs allows file names to be updated at runtime to be content hashed. This removes the need for the extra "304 Not Modified" API calls from the client. This content hash based file renaming is usually done using a build step which renames files. For applications where the static file serving and HTTP request processing are done in the same application, this can be done in memory without a build step for file renames.

I am using that approach in my project https://github.com/claceio/clace. It removes the need for a build step while making aggressive static file caching possible.

I am building https://github.com/claceio/clace. It is focussed on building operational web apps, with a focus on security. The end goal is to build something between https://www.rundeck.com/ and https://retool.com/, allow automation of operational tasks through a web interface while also allowing fully custom web apps.

Clace also works great for running simple web apps locally. Building and deploying a web app should be as easy and common for backend engineers as creating a CLI app is.

Hypermedia based web applications are a great fit for developing internal and operational tools. I have been building https://github.com/claceio/clace for making development and deployment easier for such web apps.

I have been building a project https://github.com/claceio/clace which aims to make building hypermedia based web applications easier. Clace is implemented in go, it uses Starlark (python syntax subset) for application configuration. With Clace, the apps are implemented using Starlark and (go) html templates, HTMX is used for web interface, app developer does not need to write any JavaScript.

Starlark in go https://github.com/google/starlark-go is a great way to combine the best of both, the ease of use of Python and the simplicity of go.

I have been building a platform for deploying internal web applications using this approach https://github.com/claceio/clace. Use Starlark to configure the application, the platform itself is built in go.

I have used this approach for internal tools and it has been great. It makes it much easier for one person to build the whole app, frontend and backend, and makes ongoing maintenance much easier.

I am working on https://github.com/claceio/clace which takes this no build approach and makes it easy to build portable applications, using Starlark running in go to configure the backend.

> 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.