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None of V8, JavaScriptCore, SpiderMonkey do allocation removal, which is the single most important optimization PyPy and LuaJIT do, which also goes back to Psyco. I think it is unknown how to do this well in method JITs.

Allocation removal by partial evaluation in a tracing JIT: http://dl.acm.org/citation.cfm?id=1929508

Allocation Sinking Optimization: http://wiki.luajit.org/Allocation-Sinking-Optimization

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> None of V8 .. do allocation removal

This is not correct. V8 does sink allocations into deoptimization exits. It does not sink allocations out of the loops at the moment though.

> I think it is unknown how to do this well in method JITs

I don't think it is unknown. The main simplification for tracing JITs comes from the fact that deoptimization and loop-exit can be elegantly treated within the uniform framework, which is a little bit harder for method JIT and you need to find right place to insert materialization instruction after the loop based on post-domination. Nothing hard or unsolvable though.

Yet V8, etc, perform pretty well. Is there a reason to believe allocation removal is particularly more important for Python than JS? It might be, I haven't thought about it, but at first blush that doesn't seem to be the case.

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