wabt VS Halide

https://github.com/WebAssembly/wabt/blob/main/wasm2c/README.... is a straightforward way to take an untrusted application (compiled already to wasm) and turn it into C that you can embed into your application or compile to a linkable DLL. I believe this approach has been used to sandbox untrusted libraries in production by Mozilla: https://hacks.mozilla.org/2021/12/webassembly-and-back-again...

As long as this is happening, might as well try some of my favorites: https://github.com/wasm3/wasm3, https://github.com/WebAssembly/wabt, https://github.com/bytecodealliance/wasmtime

This seems sort of like understanding machine code vs assembly; it's much easier to learn WAT and translate to/from WASM as necessary using the wabt tools [0].

Either way its super cool how simple WebAssembly is, you can really get your hands dirty and understand exactly every detail of how your program runs!

[0] https://github.com/WebAssembly/wabt

You mean this? https://github.com/WebAssembly/wabt/blob/main/wasm2c/README....

That seems like quite an undertaking. But at that point, It would make sense to cut out WASM entirely like https://datastation.multiprocess.io/blog/2022-05-12-sqlite-i...

The .wat file can be compiled to a .wasm using wat2wasm which is part of the WebAssembly Toolkit CLI tools:

it is in C++ https://github.com/WebAssembly/wabt/blob/main/src/tools/wat2wasm.cc

I don't think you are building an application that will use Native Client technologies How to extract source code from Native Client .nexe file, migrate to WebAssembly? #1864 so that would be superfluous, and frankly, useless in your case.

I'm trying to get a basic Rust webassembly program, then porting it to C via wasm2c. The example works, but when I use wasm-bindgen and analyze it with wasm2wat, I get an import "env". The issue is that in C (wasm2c) it comes out as struct Z_env_instance_t; and I can't instantiate it (as in Z_env_instance_t env; to pass it's address to Z_wasm_client_bg_instantiate.

If CPU/GPU execution speed is the goal while simultaneously code golfing the source size, https://halide-lang.org/ might have come in handy.

This is a task where Halide https://halide-lang.org/ could really shine! It disconnects logic from scheduling (unrolling, vectorizing, tiling, caching intermediates etc), so every step the author describes in the article is a tunable in halide. halide doesn't appear to have bindings for golang so calling C++ from go might be the only viable option.

Probably would have been much easier to do 15 times in https://halide-lang.org/

The idea behind Halide is that scheduling memory access patterns is critical to performance. But, access patterns being interwoven into arithmetic algorithms makes them difficult to modify separately.

So, in Halide you specify the arithmetic and the schedule separately so you can rapidly iterate on either.

It is not the sorting per-se which was improved here, but sorting (particularly short sequences) on modern CPUs with really the complexity being on the difficulty of predicting what will work quickly on these modern CPUs.

Doing an empirical algorithm search to find which algorithms fit well on modern CPUs/memory systems is pretty common, see e.g. FFTW, ATLAS, https://halide-lang.org/

Halide https://halide-lang.org/

It doesn’t apply in this case, but in general if you really want the best vectorization I would suggest using https://halide-lang.org instead of trying to coerce your compiler.

If we drop the "APL" requirement, wouldn't Halide fit your criteria for the third?