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Comment by brianolson | Hacker News Reader

If you need multi-core for performance, first you should rewrite in a compiled language instead of Python. Java/C/C++/Go/FORTRAN/whatever will run 10 to 20 times faster before even worrying about running multi-core.

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On a mid-range desktop PC, the horsepower breakdown is something like: 100% everything, 75% GPU, 25% all CPUs, 5% one CPU including SIMD, 1% a single CPU running scalar code.

I love Python. But, it's good to remember sometimes that it runs at about 1% efficiency compared to well-optimized C. So, you paid for a whole machine and you are utilizing 0.01%. That's fine for a lot of tasks; especially tasks that are 99% I/O-bound or tasks that are just coordinating big C libraries to do 99% of the work. Just good to remember sometimes...

Hedging around these statements is important, but far too often I see people convinced they are in the 1% of tasks that truly need top level performance. Which is to say, I often see people who are wrong.

It is mostly done already, if you consider numpy. But the top-layer glue code, which is Python, needs to allow it to tun in parallel, where it's not automatic.

Python is compiled language.

That is technically correct, but not useful for the conversation...

No it's not. That's like (and I know this has been said again and again) that "War and Peace" is a hardcover book. It's a non-sequitur.

Python can be compiled, interpreted, or translated into smoke signals and reconstituted on the other side of the valley. It is not per se any of these things.

Sometimes you just need better performance, not necessarily blistering.

Scalable, I meant to add.

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