[vidarh]

Yes, but that locks you in to optimising for whatever you covered with your profiling. If the character of your data changes, it'll take a recompile to change how the application performs, while a JIT can potentially choose to deoptimise/reoptimise.

I'm all for "as static as possible" toolchains, but there are optimization opportunities you simply won't have with AOT, PGO or not. E.g. consider something trivial: A program doing certain image operations that depends on dimensions passed in on the command line. A JIT could optimise the inner loops for the actual operations. To get the same with AOT even with PGO would be totally unable to deal with it without causing a massive explosion in code size.

[pjmlp]

Hence why .NET also has MPGO, Managed Profile Guided Optimizations for NGEN.

https://msdn.microsoft.com/en-us/library/hh873180(v=vs.110)....

[srean]

In theory yes, but sadly i have never seen that promise realized in any consistent fashion. Same goes for Java's escape analysis. Although the principle is sound i think the engineering required is horrendously difficult to make it robust. In a very narrow window of variation it works, but should you step out of that zone it fails pretty badly. I think it will take many more years, till then pgo and metaprogramming it is.

[pjmlp]

Regarding escape analysis, beware that the OpenJDK is the worst of them all.

IBM J9, Graal are much better at it, and I bet Aonix, Azul and other JDKs targeting high performance deployment scenarios are even better.

[mike_hearn]

Speculative optimisations yield about a 20% improvement in Java and more for higher level languages like Scala (and for Ruby it's off the charts). HotSpot isn't perfect by any means and C2's EA is not strong enough, but it's on track to be replaced with Graal (which is a part of what AOT is all about - you don't want your VM compiling itself at the same time as compiling your app).