The Dynamic Language Runtime has significant performance improvements over traditional interpreters for Python and Ruby, once it is warned up. But for code you only use once or twice, it costs more to compile the expression tree than to simply interpret it.
The DLR solves this issue by introducing what they call an Adaptive Compiler. Normally the DLR will interpret expression trees instead of compiling them. If it sees a given tree is used repeatedly, then it will compile it in a background thread to be used by future calls. According to Microsoft, this is giving IronPython 2.6 a significant performance boost over earlier versions.
Because this technology is backed into the DLR, any dynamic language targeting it may opt-in for this behavior.
Community comments
Benchmarks
by Doug Winter,
Re: Benchmarks
by Ex Raven,
Re: Benchmarks
by Doug Winter,
Re: Benchmarks
by Jonathan Allen,
Benchmarks
by Doug Winter,
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So, are there any benchmarks of this new DLR against the CPython implementation? It would be great to see if it really does deliver that much better performance.
Re: Benchmarks
by Ex Raven,
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Here's a link that might be useful to you: CodePlex: IronPython Performance
Re: Benchmarks
by Doug Winter,
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Very very mixed, if I am reading those results correctly.
I'd generally take benchmarks with a pinch of salt, but I have to say I think they have some more work to do on the DLR yet ;)
Re: Benchmarks
by Jonathan Allen,
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Once they have Python 2.6 compatibility, they are shifting their focus to performance. Up until now they have been playing catch-up, but they expect to have some breathing room while Python plans their 3.2 feature set.