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PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

morepypy.blogspot.com

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Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#41

Post by baldfat »

pjmlp wrote: post #8
wyldfire wrote: post #5

Kudos to the pypy team! I suspect pypy would benefit from some kind of marketing campaign. It rarely lets me down and yet lots of python devs don't know about it. The most popular package(s) that don't work with it have been numpy, scipy, etc. When I first encountered pypy, there was a numpypy and I wouldn't be surprised if that's different now. But bottom line, tons of python code out there needs more performance an…

> But bottom line, tons of python code out there needs more performance and has no dependency on numpy or any C extensions. What they need is nice JIT engines like PyPy and not to switch languages. If no one invested in improving implementations for modern languages and switched to something lower level all the time, we would still be using Fortran for business applications.

We still are using FORTRAN for Business Applications and I fail to see the need to switch them to a slower language to modernize them. Unless the switch is solving a program leave them alone. This is why in R there is still plenty of FORTRAN code.

Personally I LOVE Python but I always feel it is the 2nd best choice. I do use Python but it rarely is the best tool to use for the problem you are solving. Maybe Pypy will turn this around, and I hope so.

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#42

Post by Beltiras »

canjobear wrote: post #28

It's hard to tell from these posts under what circumstances will SIMD vectorization kick in outside of numpy. E.g., will it work for plain old list comprehensions, which are everywhere in my code? That would be awesome.

I did a small test, here's the gist:https://gist.github.com/arnists/a9f19af5d9469549020e

Seems like a huge improvement, don't know if it's the recent additions or in general pypy vs cpython but it's enough of a speed bump to sit up and take note.

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#43

Post by fijal »

sandGorgon wrote: post #32
fijal wrote: post #6

Earlier quoted context omitted.

we're trying to address both numpy and C extensions, stay tuned ;-)

you should kickstarter this - and also the python 3 support.

we did kickstart the python 3 support on our website. Donate!

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#44

Post by fijal »

dorfsmay wrote: post #35
fijal wrote: post #27

Earlier quoted context omitted.

Try builtin json instead of simplejson for pypy (it's API-equivalent)

On big jobs (millions of json input/output) I have found ujson significantly faster than json + pypy.

yop, as I said, ujson is probably your best bet if all you do is parse json.

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#45

Post by Zancarius »

MatthewWilkes wrote: post #37
forgotpwtomain wrote: post #25

Earlier quoted context omitted.

Personally I'd be quite excited to see a bug I reported fixed the same-day - of course people's expectations are different it's not always easy to balance these things.

I can understand that, I certainly would have been stoked about a bug report being fixed on the same day; I hadn't reported the bug though. I was working on providing a bug report with a patch alongside it and (perhaps foolishly) mentioned the bug informally as context as to why I was doing this.

Without being privy to the entire context, what I think might've happened is that your discussion caught the interest of a core developer who then picked it up and ran with it. I doubt they intended to step on your toes as a consequence of fixing the problem. Hackers tend to be intrigued by problems, including small ones, and especially ones that cause software behavior to deviate from expectations.

The other side of the coin is that without a patch, the developers have no idea what your motives or capabilities are. They can't read minds, so if you pique their interest sufficiently, they're very likely to take it upon themselves to do the legwork. No malice intended. I should hope you'll change your mind about contributing to FOSS projects after reading this thread, because I think it's counterproductive to take this sort of thing personally (I don't know if you are, but it appears to me that you're unhappy about this at the very least).

That said, there aren't many projects that post credits or thanks to people who have discovered bugs or whose line of questioning has lead to fixing application behavior. While it's extra work and isn't always feasible, it can encourage users to pitch in if they know their name might appear in some credits (even if it's only per-release). Then there's the question of how big the problem needs to be to credit someone...

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#46

Post by ant6n »

gdulli wrote: post #19

My experience with PyPy was that it was faster for mapreduce jobs without JSON parsing and slower for JSON-heavy jobs. Because, I assume, CPython benefits from a C implementation of simplejson and PyPy doesn't. Does anyone know if this has changed? (I'll probably install 4.0 and see for myself, but curious if anyone knows what I should expect.)

One has to be careful with strings in pypy, because they don't have a string-builder optimization. Or maybe they do now?

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#47

Post by jordigh »

fijal wrote: post #23
jordigh wrote: post #18

I wish it had faster startup time, which really matters for Mercurial.

Working on it (even wrote 2 blog posts recently about it). Mercurial is an interesting benchmark/use case for us.

Yay! Glad to hear it. Using Python makes me so envious of Perl's startup time. Maybe some day we can have that in Python too...

Where are those blog posts?

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#49

Post by fijal »

jordigh wrote: post #47
fijal wrote: post #23

Earlier quoted context omitted.

Working on it (even wrote 2 blog posts recently about it). Mercurial is an interesting benchmark/use case for us.

Yay! Glad to hear it. Using Python makes me so envious of Perl's startup time. Maybe some day we can have that in Python too... Where are those blog posts?

https://morepypy.blogspot.pt/2015/10/pypy-memory-and-warmup-...

https://morepypy.blogspot.pt/2015/09/pypy-warmup-improvement...

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#50

Post by cfontes »

wyldfire wrote: post #5

Kudos to the pypy team! I suspect pypy would benefit from some kind of marketing campaign. It rarely lets me down and yet lots of python devs don't know about it. The most popular package(s) that don't work with it have been numpy, scipy, etc. When I first encountered pypy, there was a numpypy and I wouldn't be surprised if that's different now. But bottom line, tons of python code out there needs more performance an…

I am a Java dev, I heard of PyPy a few years ago, I find it amazing and often tell people about it when talking about performance and other related topics.

The thing is I've never found another developer that new about it, something is very wrong...

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