blog

ptorJIT project, a fork of LuaJIT apparently intended to turn it into something maintainable by mere mortals: https://github.com/lukego/blog/issues/19 - some videos here: https://www.youtube.com/@lukego/streams

better and sense which parts of the program were essential enough to re-type. He thought this was the most natural thing in the world: of course you throw away the first few implementations, you didn't understand the problem when you wrote those! [0] https://github.com/lukego/blog/issues/32

want a robust engine that can handle whatever weird code the web is throwing at you, tracing JITs are (as far as I can tell) a dead end. (Counterpoint: LuaJIT seems to be doing alright with tracing, although it may just solve the problem by punting to the programmer: https://github.com/lukego/blog/issues/29. That's more feasible when you don't have multiple engines with performance cliffs in subtly different places.) Second, the idea that JIT-compiled code can be faster than AOT-compiled code has been floating around for a long time, but I don't think it really holds in the general case. Doing work at runtime isn't free: not just time spent compiling, but also time spent profiling and validating that your speculative optimizations continue to be correct. SpiderMonkey had a top-tier optimizing compiler, IonMonkey, that got pretty darn close to native code on hot benchmark loops. We tracked whole-program information to ensure that type checks could be elided in inner loops. (For example, if the `x` property of a certain set of objects only ever contained 32-bit integers, then we could unbox it without checking the type. If any code elsewhere ever stored a non-integer value in that property, we would notice and invalidate the optimized code.) We threw IonMonkey away, because it was too brittle. In practice, real-world code falls off the happy path often enough that we got better performance by accepting that even your highly optimized JS code will include some runtime checks. Invalidation and recompilation are real costs. So is the upkeep of all the global data necessary to support Ion. There's an engineering tradeoff between pushing up the performance ceiling and bringing up the performance floor; we've been happy with our choice to shift focus more towards the latter. Our numbers are down on artificial benchmarks, but it seems to have paid off in real-world performance. (Also, bugs in the optimizing compiler are significantly less likely to be exploitable.) A lot of really smart people have done some incredible work on the JVM. Nevertheless, I'm still not aware of any code written in Java instead of (say) C++ or Rust because Java was faster. I think it's more accurate to say that JIT compilation can be fast enough that the other advantages of the language can make it the right choice.

epeat this process five or six times (program5, program6, ...) and each time he would understand the problem a little better and sense which parts of the program were essential enough to re-type. He thought this was the most natural thing in the world: of course you throw away the first few implementations, you didn't understand the problem when you wrote those!