hal9ai VS design

We are not using libfortran not gdpr, we are basically using whatever libraries are available for the web. Since most data scientists don't want to use JS per se, you can build the apps as blocks in the Hal9 site or using a soon-to-be-released Python/R package, see https://notebooks.hal9.com

Feel free to check out our repo as well, all the "primitives" / blocks code is in the scripts folder: https://github.com/hal9ai/hal9ai

https://hal9.com helps data scientists build faster web applications.

It uses WebGL and WebAssembly to process larger datasets, perform inference in the browser with TensorFlow.js, and enables running Python code with Pyodide.

If you want to build a web application on top of your ML project, give https://hal9.com a shot. We designed Hal9 with ease of use for deployment and maximum compatibility with web technologies that enable you to build ML apps with React, Vue, etc. We launched a couple months ago but could use some early feedback and users. Thank you!

BTW. If you are ever interested in helping us out, you can send a PR's to our GitHub repo. For instance, the summarize and convert blocks are here: https://github.com/hal9ai/hal9ai/blob/main/scripts/transforms/summarize.txt.js and https://github.com/hal9ai/hal9ai/blob/main/scripts/transforms/convert.txt.js

We are working in https://hal9.com which is language agnostic and allows you to compose different programming languages; however, we are focused at the moment at 1D-graphs but have plans to support 2D-graphs in the coming weeks.

If you want a demo or just time to chat, I'm available at javier at hal9.ai.

We would love to help out since this is a perfect use case for https://hal9.ai; we are about to release our beta version that makes this as easy as copy-pasting code. You can find me at javier at hal9.ai to find some time to chat and give you a walkthrough of our code-to-api functionality.

Hi there, would love to help you out. We are building a JavaScript + Python/R/AI service called https://hal9.ai to enable you to build React/Vue/Svelte/Angular apps against Python/R models. Want to send me an email to javier at hal9.ai to chat and help out?

Would love to hear your feedback for https://hal9.ai -- We are building an open source platform for data analysis based on reusable code blocks and a community to build and monetize their contributions. We are pretty early in our journey, launched our alpha and getting ready for our beta release, but would love to hear your thoughts. You can find me at javier at hal9.ai. Cheers!

With WebAssembly we can compile our C++ codebase into a wasm module for the browser. So when you look at a SciChart.js chart you're actually seeing our C++ graphics engine wrapped for JavaScript.

I should add, however, that the unmentioned elephant in the room is V8 JIT (TurboFan), which simply doesn't handle irreducible control flow. While there are some valid theoretical arguments around the current arrangement in Wasm, looking at the history of the associated discussions makes it pretty obvious that having V8 support Wasm and generate fast code similar to what it can do for asm.js was an overriding concern in many cases. And Google straight up said that if Wasm has ICF, they will not bother supporting such cases, so it will be done by a much slower fallback:

https://github.com/WebAssembly/design/issues/796#issuecommen...

AFAIK no other Wasm implementation has the same constraint - the rest generally tend to desugar everything to jumps and then proceed from there. So this is, at least to some extent, yet another case of a large company effectively forcing an open standard to be more convenient for them specifically.

https://github.com/WebAssembly/design/issues/1397

> Currently allocating more than ~300MB of memory is not reliable on Chrome on Android without resorting to Chrome-specific workarounds, nor in Safari on iOS.

That's about allocating CPU memory but the GPU memory situation is similar.

As far as I can tell (5 minutes of internet research) this was to allow easier compilation to JavaScript as a fallback in the days when WASM wasn't widely supported.

"Please add goto" issue has been open since 2016:

https://github.com/WebAssembly/design/issues/796

Most interesting comment:

> The upcoming Go 1.11 release will have experimental support for WebAssembly. This will include full support for all of Go's features, including goroutines, channels, etc. However, the performance of the generated WebAssembly is currently not that good.

> This is mainly because of the missing goto instruction. Without the goto instruction we had to resort to using a toplevel loop and jump table in every function. Using the relooper algorithm is not an option for us, because when switching between goroutines we need to be able to resume execution at different points of a function. The relooper can not help with this, only a goto instruction can.

> It is awesome that WebAssembly got to the point where it can support a language like Go. But to be truly the assembly of the web, WebAssembly should be equally powerful as other assembly languages. Go has an advanced compiler which is able to emit very efficient assembly for a number of other platforms. This is why I would like to argue that it is mainly a limitation of WebAssembly and not of the Go compiler that it is not possible to also use this compiler to emit efficient assembly for the web.

^ https://github.com/WebAssembly/design/issues/796#issuecommen...

When I implemented a WASM compiler, the only source of float-based non-determinism I found was in the exact byte representation of NaN. Floating point math is deterministic. See https://webassembly.org/docs/faq/#why-is-there-no-fast-math-... and https://github.com/WebAssembly/design/blob/main/Nondetermini....

> To work with GC, you need some way to track if the GC'd object is accessible in WASM itself.

I've never heard of a GC with that kind of API. Usually any native code that holds a GC reference would either mark that reference as a root explicitly (eg. https://github.com/WebAssembly/design/issues/1459) or ensure that it can be traced from a parent object. Either way, this should prevent collection of the object. I agree that explicitly checking whether a GC'd object has been freed would not make any sense.

> The reason why you probably need a custom string type is so you can actually embed string literals without relying on interop with the environment.

WASM already has ways of embedding flat string data. This can be materialized into GC/heap objects at module startup. This must happen in some form anyway, as all GC-able objects must be registered with the GC upon creation, for them to be discoverable as candidates for collection.

Overall I still don't understand the issue. There is so much prior art for these patterns in native extensions for Python, PHP, Ruby, etc.

Giving you a buffer that grows is the allocation approach I am talking about. This is not how your OS works. Your OS itself works with an allocator that does a pretty good job making sure that your memory ends up not fragmented. Because WASM is in between, the OS is not in control of the memory, and instead the browser is. The browser implementation of "bring your own allocator" is cute but realistically just a waste of time for everybody who wants to deploy a wasm app because whatever allocator you bring is crippled by the overarching allocator of the browser messing everything up.

It seems like the vendors are recognizing this though, with firefox now having a discard function aparently!

https://github.com/WebAssembly/design/issues/1397

Scientific performance critical code isn't written in Python, it is written in C/C++ which is used by Python. Python in ML usually merely describes the calculation not unlike React describes the DOM that should be displayed in the browser.

JavaScript was never really known for admin or file manipulation (Perl replacement), so that was what probably established the dominant ecosystem for Python. I also don't think the runtime overhead is applicable due to native C/C++ part, and download time doesn't have to be bad since modules can be split just like in JavaScript ecosystem today. For an AI app, the model inference weights might be larger than the compiled WASM code itself. However, I'd agree with you that porting legacy apps might not be possible without something close to a rewrite.

There is a reasonable chance that once WASM GC is implemented, then direct DOM access will be provided [1], which I believe could pretty much halt interest in new JavaScript development for web frameworks overnight. WASM is the reincarnation of the Java Applet, but better. And a more typed language like Go or Dart could become the most widely used programming language. Either compile it to WASM as plugin for something like the browser, compile to JavaScript for "legacy browsers", or to native code for a standalone app. There are probably a handful of developers already assuming this and trying to write a version of React running in WASM already.

[1] https://github.com/WebAssembly/design/blob/main/Web.md#gc