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Comment Re:The article isn't great for the lay-person (Score 1) 114

I haven't the foggiest idea how a temperature gradient can cause matter to climb out of a gravity well.

Thermophoresis causes particles in a fluid to move because of a temperature gradient. The similarity parameters (Reynolds / Mach / Knudsen) for a planetesimal in an accretion disk are probably similar to the aerosal particles in air that the wiki article talks about.

Comment Re:Statistical analysis of the summary (Score 1) 572

To make any statements, you would first need to make some observations

Or you could be a Bayesian, make some assumptions, include a priori info in the analysis (which you should probably do anyway even if you have data); before you get up to check if there is an elephant in the kitchen assigning equal priors to the two hypothesis is a sound maximum entropy sort of method. You can then update your 50/50 state of knowledge after observing zero or many elephants in your kitchen.

Comment Re:Everyone should learn statistics (Score 1) 572

"the data comes from an underlying normal distribution"

You mean we often assume the residuals are normal; the data could be any distribution at all, that's why we fit models. There's plenty of parametric stuff you can do with different distributions on the residuals too; Google "R glm Poisson", "R glm binomial", or "R glm family".

You might already know all this, but ever since that black swan book came out there's a bunch of statistical-illiterates running around saying, "the whole world's not normal", without understanding that everybody who understands the world and statistics understands that already too.

Comment Re:That's why I have a problem with the comparison (Score 1) 127

Take a problem that is all 64-bit integer math and has a branch every couple hundred instructions and GPUs will do for crap on it.

So would a Cray; supercomputers and GPUs are made for the same sorts of problems (exploiting data parallelism). Now if by 'supercomputer' you mean 'a cluster of commodity hardware', then ok, you've got a point, that heap of cpus will handle branches plenty fast.

Comment Re:How fast is this really? (Score 1) 127

Well, I'm not sure about most of your criticisms, but they use Jacobi instead of Gauss-Seidel because SSOR is not data parallel, but Jacobi is.

That would make the performance the same as for the GPU system.

Really? Care to share any results that support that? I'm quite sure the peak flops you can achieve on the GPU are much higher than the limited SIMD capability of the CPU.

Note that I am being generous here and actually ignoring the program setup time when they need to copy the data to the GPU.

Sure there's communications overhead, but that's true of any parallel processing problem, the trick is to find problems that have a big computation to communication ratio (which happens to be most of computational physics and these tomographic reconstruction problems that TFA mentions as well).

Comment Re:How fast is this really? (Score 2, Informative) 127

you can get absolutely incredible performance out of off-of-the-shelf GPUs these days.

I had heard this from folks, but didn't really buy it until I read this paper today. They get a speed-up (wall clock) using the GPU even though they have to go to a worse algorithm (Jacobi instead of SSOR). Pretty amazing.

Comment Re:Intel (Score 1) 230

Intel's compiler is actually one of the best optimizing compilers out there (when it doesn't detect an AMD processor and not bother doing the optimizations...).

I'll second that, here's an example from the Octave mailing lists:

To conclude, on my computer, for this test, Octave is approximately as fast as C, gfortran is a little bit faster and ifort is 10 times as fast.

For scientific computing it's tough to beat ifort on intel iron.

Comment Re:re Time for open discussion (Score 1) 1093

It's that to say that some random blogger likely doesn't have the tools to correctly analyze the data

Most of the palaeoclimatology stuff is just curve fitting, they use Matlab (Octave) and R (read the emails), so yeah, some random blogger actually would have the tools that the 'pros' use quite readily available. The silly thing with the paleo stuff is that it is so easily reproducible if you have access to the data, that's why there's a bit of empire building by data hoarding in this community.

Comment Re:Oink! Oink! (Score 1) 209

Back-of-the-envelope overhead comparison:
  • (from the wiki): The Augustine Commission also stated that Ares I and Orion would have an estimated recurring cost of almost $1 billion per flight.
  • (from SpaceX site): 44-49.5M depending on the orbit you want (LEO or GTO), that's the 'out the door' price (not the cost), sure that doesn't include the cost of the payload

The costs are not even in the same order of magnitude, you really think SpaceX's Dragon will add additional recurring costs of $950M? The performance improvement from Falcon 9/Dragon to Ares I/Orion is incremental, certainly not enough to justify the price difference (unless you happen to work at MSFC / Boeing / Lock-Mart).

Comment Re:Oink! Oink! (Score 2, Informative) 209

Yeah, those DoD contracts where he actually (attempted) to put stuff in orbit...what pork! They weren't paying him for power point slides...

Apparently Falcon 1 / SpaceX startup costs are around $450M, which is about what that recent Ares I-X test flight costs. You think there might be a little difference in the overhead of the two operations?

I'm not arguing against the conservation of energy, (yeah lots of energy to get something to LEO), just that there might be a better way.

Comment Re:Oink! Oink! (Score 1) 209

You don't need decades of experience to have an opinion about the usefulness of giving a select few joy rides into space.

The assumption that any project NASA attempts needs to take deca-years and giga-bucks is part of the problem. Small is beautiful, those decades long development projects you (and the big aero-defense contractors) love are not.

A little 'buck-up' by NASA management is a good thing.

Comment Re:Calling Pons and Fleischmann... (Score 1) 1747

The deviation since 1960 doesn't automatically mean that the records are wrong before 1960, as the instrumental records validate a large chunk of the pre 1960 period tree ring proxy data as correct within a given error bar. Noone knows the reasons why the tree ring proxy data is wrong "recently", but it is entirely possible that the cause is something like "more recent rings on trees take time to dry out" or something like that. It would be interesting to find out the cause.

And no one knows if they were wrong in the past in a similar way; that is the danger of chasing correlations without a firm grasp of the physical mechanisms (which provide model structure and make extrapolation beyond the calibration region somewhat safe).

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