On Wed, Sep 9, 2015 at 9:47 PM, Tim Peters <tim.peters@gmail.com> wrote:

[Tim, on parallel PRNGs]

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There are some clean and easy approaches to this based on crypto-inspired schemes, but giving up crypto strength for speed. If you haven't read it, this paper is delightful:

http://www.thesalmons.org/john/random123/papers/random123sc11.pdf

[Nathaniel Smith]

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It really is! As AES acceleration instructions become more common (they're now standard IIUC on x86, x86-64, and even recent ARM?), even just using AES in CTR mode becomes pretty compelling -- it's fast, deterministic, provably equidistributed, *and* cryptographically secure enough for many purposes.

Excellent - we're going to have a hard time finding something real to disagree about :-)

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(Compared to a true state-of-the-art CPRNG the naive version fails due to lack of incremental mixing, and the use of a reversible transition function. But even these are mostly only important to protect against attackers who have access to your memory -- which is not trivial as heartbleed shows, but still, it's *waaay* ahead of something like MT on basically every important axis.)

Except for wide adoption. Most people I bump into never even heard of this kind of approach. Nobody ever got fired for buying IBM, and nobody ever got fired for recommending MT - it's darned near a checklist item when shopping for a language. I may have to sneak the code in while you distract Guido with a provocative rant about the inherent perfidy of the Dutch character ;-)

:-) Srsly though, we've talked about switching to some kind of CTR-mode RNG as the default in NumPy (where speed differences are pretty visible, b/c we support generating big blocks of random numbers at once), and would probably accept a patch. (Just in case Guido is undisturbed by scurrilous allegations.) -- Nathaniel J. Smith -- http://vorpus.org

On Wed, Sep 9, 2015 at 9:47 PM, Tim Peters <tim.peters@gmail.com> wrote:

[Tim, on parallel PRNGs]

...

...

There are some clean and easy approaches to this based on crypto-inspired schemes, but giving up crypto strength for speed. If you haven't read it, this paper is delightful:

http://www.thesalmons.org/john/random123/papers/random123sc11.pdf

[Nathaniel Smith]

...

It really is! As AES acceleration instructions become more common (they're now standard IIUC on x86, x86-64, and even recent ARM?), even just using AES in CTR mode becomes pretty compelling -- it's fast, deterministic, provably equidistributed, *and* cryptographically secure enough for many purposes.

Excellent - we're going to have a hard time finding something real to disagree about :-)

...

(Compared to a true state-of-the-art CPRNG the naive version fails due to lack of incremental mixing, and the use of a reversible transition function. But even these are mostly only important to protect against attackers who have access to your memory -- which is not trivial as heartbleed shows, but still, it's *waaay* ahead of something like MT on basically every important axis.)

Except for wide adoption. Most people I bump into never even heard of this kind of approach. Nobody ever got fired for buying IBM, and nobody ever got fired for recommending MT - it's darned near a checklist item when shopping for a language. I may have to sneak the code in while you distract Guido with a provocative rant about the inherent perfidy of the Dutch character ;-)

:-) Srsly though, we've talked about switching to some kind of CTR-mode RNG as the default in NumPy (where speed differences are pretty visible, b/c we support generating big blocks of random numbers at once), and would probably accept a patch. (Just in case Guido is undisturbed by scurrilous allegations.) -- Nathaniel J. Smith -- http://vorpus.org