C/C++ developers rely on knowledge of compiler optimisations all the time, the most famous case being the NRV optimization in C++. But exploiting knowledge of w

C/C++ developers rely on knowledge of compiler optimisations all the time, the most famous case being the NRV optimization in C++. But exploiting knowledge of where data structures will be allocated is another example. Java can be used for numerical work but it's not ideal for the reasons you cite. However this isn't fundamental to the technology or language. It's more a problem of incentives. Java isn't used for such work, so the applications that people care about and try to optimise at the JVM level don't tend to benefit from them, so the cost/benefit ratio of such optimisations seem low, so focus goes elsewhere. C2 can do quite sophisticated auto-vectorisations but I suspect those optimisations rarely trigger because work that benefits from vectorisation was moved into C or assembly a long time ago. It's rather forward looking work. Graal doesn't even focus on it. They put all their effort into optimising large 'business java' type apps, along with language interpreters (Graal's party trick is turning interpreters into fast JIT compilers).