="Joerg Arndt" <arndt@jjj.de> As some of us are interested in random number generation, I'd like to point to https://www.cs.hmc.edu/~oneill/ I'll unlike find time to read the paper (preprint as of now), so comments are welcome.

Comments? Heh, be careful what you wish for! I'll try to be brief, but this provokes a pet peeve (please delete if unfun)... I skimmed the paper, and at risk of missing something of value, I'll also pass on chewing deeper into all that verbal excelsior because I think it's ultimately a huge waste of time. My opinion is that academics have created a tiny but evergreen cottage industry around PRNG design for decades by presuming the problems they are addressing are actually interesting. One of the biggest outdated misapprehensions is that, while it may have been vital to minimize internal state in the von Neumann era, today it's just quaint. After progressive decades of "Moore's Law", statements like the following from the paper sound like outtakes from a "Downton Abbey" episode: "If the entire state of a random number generator can be represented in a single processor register, we may reasonably expect it to offer performance advantages compared to a generator that requires hundreds or thousands of bytes of memory to represent its state." Confining attention to algorithms operating on a single register is like insisting on programming while peeping through a keyhole. A nice circus stunt if one can pull it off perhaps, but of little real relevance today. As much as I love Don Knuth, I think he, with the best of intentions, did the art a disservice by obsessing at such length in TAOCP over the Linear Congruential Generator. I suspect in part this was because there was such a sunk investment in all that pretty analysis. I regret that a consequence has been a pernicious misplacement of priorities, resulting in blizzards of this kind of misdirected academic snow ever since. But what's done is done. Ironically, TAOCP actually briefly treats some alternative approaches with much longer legs. Here's an example I've used, thanks to a suggestion by Bill Gosper: ======== implementation sketch ======== Take the structure of a classic 1965 "Tausworthe" (circular-shift-with-XOR) bit generator, expand each of the BITS to an entire WORD, and add (rather than XOR) their values to get the next output word. So a classic 64-BIT (say) shift-register generator expands into a 64-WORD generator (now with 4096 bits of state). This is incredibly trivial to implement and very fast: a circular buffer of 64 "registers" (that will be cached in fast memory of course), a handful of auto-incrementing pointers and some additions. Not even multiplies or mods. Now look at the LSB of the outputs. This will be the sequence of bits the Tausworthe generator produced. But furthermore, the higher order bits will be likewise, except that they will be perturbed by the cascade of "noise" carries coming out of the lower-order bits. This has a huge state space and hence period (if you're obsessed with that) and I expect is more than plenty good for almost any practical purpose. However if you're worried about an adversary that's reading the output stream and trying to invert it, then you can mess up the rigid time correlations by adding a scrambling post-process (also essentially described in Knuth) as follows: Take the upstream generator, call it R1, a second table T2 (likewise initialized with noise) and some other generator R2 (actually R1 and R2 could probably just be alternating outputs of the wide-Tauseworthe thingy). Output T2[R2}, then increment T2[R2] += R1. Now T2 is accumulating a turbulent rain of the noise from R1, mixed by R2. ======== end of implementation ======== This thing is cheap to implement, very fast and easy to understand and test. But, also probably less fun for academic analysis (due to being both too easy and too hard). And of course 2048 bits, or even a megabit, is a pittance nowadays. Think it'd work? Maybe we can stop churning out papers about new PRNGs? PS: for an interesting alternative for fast clean noise, but with different design criteria (basically NO state update, F[n] vs. F[F[...), see John K. Salmon, Mark A. Moraes, Ron O. Dror, and David E. Shaw, "Parallel Random Numbers: As Easy as 1, 2, 3," Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC11), New York, NY: ACM, 2011.