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PyPy and Psyco

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Re: PyPy and Psyco

#11
post #10
post #9

Earlier quoted context omitted.

Raw execution speed does matter, but like any incremental cost, is often ignored. Off-the-cuff benchmarks I ran on our Scala-based webapp on a four-core desktop system demonstrated 5,000 req/sec @ 2ms/request after the JIT warmed up. 5,000+ requests/second -- scaling up with available CPUs -- means not having to worry about performance, complicated caching, and the slew of other things that developers do to eek perfo…

It's not really an incremental cost but rather a constant overhead. The idea is that if you're worried about performance and scaling then you'll have to find a way to distribute your load over multiple physical machines anyways. At that point it doesn't matter so much anymore whether one of your nodes handles 5000 reqs/sec or 2500 reqs/sec. Hardware is cheap.

"Hardware is cheap" is a false dichotomy. The implication is that hardware is cheap, but development is not, and performant architectures require expensive development.

In reality, neither hardware or development are cheap, and performance does not inherently necessitate more costly development. The mantra and the dichotomy are false.

Re: PyPy and Psyco

#12
I recently wrote some image-manipulation routines in Python which ran 71 times faster with Psyco. Without Psyco, this kind of computation isn't really feasible in pure Python, so I'm also a little surprised Psyco hasn't had more influence on C Python. But perhaps its just a matter of time before PyPy is bequeathed Psyco optimizations.
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