Fascinating. I've written cross platform (WASM, iOS, Android) libraries with Rust before and had a good time but Rust can be a pain too. Cross-platform Typescript is a really interesting proposition.
That said, the more I think about it the more dubious I am. The site boasts no runtime dependencies but clearly it’s going to need things like a garbage collector, you can’t just magic that requirement away. At a certain point is it just doing what a JS engine’s JIT compilation does… except ahead of time?
Also doesn't inspire confidence that the text on the site is very clearly AI generated and the GitHub log shows an endless stream of AI powered commits. About 15 per hour, every hour? Doesn’t scream stability.
Perry uses NaN-boxing to preserve TypeScript's dynamic type system at runtime, the same approach as JavaScriptCore. The PERF_ROADMAP is honest about the cost: 1.86x behind Zig on image convolution, with 1.24 billion wasted instructions traced specifically to NaN-box unboxing. You cannot get C-level performance without dropping TypeScript semantics, and dropping them means you are no longer compiling TypeScript.
Typescript is a dynamic language. Without changing the language, there is fundamentaly no way to resolve at compile time decisions that can be made only at runtime (ie, they are data driven). Monomorphization helps pin down (some) dynamic types but the fundamental problem remains.
You're right. The typed buffer locals optimization keeps TypeScript semantics intact by exploiting the existing Buffer/Uint8Array type annotation to skip the NaN-unbox. It's not dropping types, it's using them. The floor I described applies to any-typed paths where static type info isn't available. For well-typed TypeScript, the roadmap shows the gap closes without semantic changes.
Curious where on spectrum compiling to wasm falls between art project & optimization potential. Should be able to make some nice interfaces between TS-wasm & TS-web
I'm not against AI usage but the website, documentation, and even the comments the creator (proggeramlug) makes in response to questions are all very clearly AI-generated. Also, as someone else noticed, the pacing of the commits is eerily fast. That combined with the level of functionality makes me dubious how much accountability the creators have over the implementation.
Like you really built a backend that lowers to LLVM, integrated it with a generational gc, wrote a cross-platform reactive runtime, and built support for eleven different targets within like a year? Are you just prompting the model to tack on the next coolest thing or do you understand how these features work?
I worry how many of these kinds of projects will show up now. How do you guarantee stability? If there's a memory corruption error in the GC implementation, who's going to debug it?
That said, the more I think about it the more dubious I am. The site boasts no runtime dependencies but clearly it’s going to need things like a garbage collector, you can’t just magic that requirement away. At a certain point is it just doing what a JS engine’s JIT compilation does… except ahead of time?
Also doesn't inspire confidence that the text on the site is very clearly AI generated and the GitHub log shows an endless stream of AI powered commits. About 15 per hour, every hour? Doesn’t scream stability.
Once you see a few, it becomes obvious
There are a bunch of tools that JIT somewhat optimized assembly.
...wait, I went and looked up that file.
"The Three Optimizations That Would Close the Gap"
You're presenting the data from there in an extremely misleading way! They in no way need to drop any Typescript semantics to go faster.
Like you really built a backend that lowers to LLVM, integrated it with a generational gc, wrote a cross-platform reactive runtime, and built support for eleven different targets within like a year? Are you just prompting the model to tack on the next coolest thing or do you understand how these features work?
I worry how many of these kinds of projects will show up now. How do you guarantee stability? If there's a memory corruption error in the GC implementation, who's going to debug it?
The models are good enough that this works.
You can keep disagreeing for a while, but know that almost all the code in the industry is written like this now.