I live in Lower Asscrack (small midwestern city) on a 1/4 acre lot and my wife and I have been composting for years. We rake the leaves and use them as mulch for the flowerbeds and garden, and compost vegetables etc. which is raked into the soil in the spring. We aren't serious about gardening but it's really no big deal and it's kind of neat to see a hundred pounds of vegetable matter/plants etc. turn into nice rich black peaty compost. After doing this for about 10 years we have some excellent soil as the leaves from years ago have turned into topsoil by now.

I lived in Boulder, CO for a while recently. There are like 5 recycle buckets. But you figure it out. For those people who are moaning about having to figure out what recyclables go where: EABOD and STFU you whiny vaginas. Such a small inconvenience clearly will not ruin you busy important lives.

Neat, but for any job that isn't embarrassingly parallel, communication latency and speed will kill you when your nodes are spread across continents. If you're not doing any communication, well then groovy. Usually these large core servers are only 'earning their keep' when you're taking advantage of very fast interconnect hardware and doing things that can't be done by just a bunch of CPUs.

Does the UK/Europe have federally funded, shared computational resources for researchers? In the US we have what used to be called the Teragrid (now XSEDE) which is a network of supercomputers that are available for researchers. You have to write a proposal for machine time, but they're not all that difficult to get. The main disadvantage is that you have to submit your jobs via a queueing system, so your jobs usually don't start right away (having your own hardware does have its advantages) but the big shared resources have their advantages - you don't have to worry about maintenance, they usually have reliable archival resources, and every X years they usually replace the hardware with something faster.

I have lived on the eastern side of the central timezone and the western side of the eastern timezone. I prefer the latter, because it means that it stays light later (on the clock), regardless of what time of the year it is. My dad lives in Maine, a stone's throw from the Atlantic time zone and it's quite a different experience for us even though we're both in the Eastern time zone. In the early summer twilight occurs at his house at 4:30 AM - yuck.

If you are an earlybird and want light early, it's best to be on the eastern side of your time zone. If you like your daylight in the evening, pick the western side. And if you want persistent albeit rather dim sunlight in the summer, move to Nome.

I stopped reading after the author said three times in the first page that science was "proving" this or that. Unless you are a mathematician, you are not proving anything. So I can't really take this guy too seriously.

The scientific process is basically about experimenting/analyzing/hypothesizing/ruminating. Good scientists are overwhelming conservative in their conclusions because good scientists understand "the box" within which they are working.

The fact that early studies are overturned with new analysis is exactly what makes the scientific process so powerful. When new studies call into question the results of earlier studies it is called progress. If a new study shows that a previous study used questionable statistical approaches, then future reviewers can cite this new knowledge to keep new studies from using these flawed approaches. The scientific process and the peer-review process is certainly not perfect, but I have yet to hear from its detractors of a better alternative.

I don't recall anything during the billions of years prior to being born. I suspect after I die it will be similar. Just nothing, and no consciousness to experience it.

Being alive is really quite a trip and a rare gift. I plan on making the best of it. Life is for the living.

No mention of the 6,475,248 correct statements in the report.

Actually, there are only a handful of variables in a weather simulation. For a typical cloud-scale simulation you have the three components of wind, moisture, temperature, pressure, and precipitation variables. Say, 13 variables. That is not why you need supercomputers.

The reason you need supercomputers to do weather simulations is all about resolution, both spatial and temporal. Weather simulations break the atmosphere into cubes, and the more cubes you have, the better you resolve the flow. All weather simulations are underresolved; to properly model the turbulent flow in the atmosphere you need to get down to cubes that are roughly a centimeter on a side. As you double the resolution (halve the length of each of the four lines that makes up a cube face) you require eight times as many cubes. In weatherspeak, we talk about gridpoints instead of cubes where it's understood that each gridpoint represents the center of one of these cubes. In the computer model, they are represented as three dimensional floating (or double precision) point arrays. So take a 3D array and double the number of calculations on each of the thee for: loops, and you've got eight times as many calculations and eight times more memory required.

And it gets worse. When you double the resolutions, you need to halve the time step. Weather models step forward in time in discrete intervals, and now in addition to more calculations for each time step (eight times as many for doubling the resolution in three dimensions) now you need to go in steps that are half as large. This means 16 times more calculations, and eight times as much memory, to double the resolution.

And many of the calculations that are being made in the innermost loop involve things like divides, non-integers powers, square roots, etc... expensive calculations. And then because it's a massively parallel simulation, you have to do internode communications - which adds overhead and can be rather a bother. Then there's the hundreds of TB of data the model is dumping to disk. Now let's render that, shall we? Somebody call Pixar.

I am working on a project to simulation a thunderstorm which will produce a tornado in a "natural" way. The tornado needs to be adequately resolved. This simulations will have grid spacing of 10 meters. It requires a computer which hasn't been fully built yet (Blue Waters, in Urbana, google it). The time step will be 0.01 seconds, and the model will run for two hours of model time. It will take days of wallclock time. Keep in mind this model will have a physical domain not much bigger than about half the area of Oklahoma. Imagine global climate modeling now, and now you're talking 4 km resolution being all you can do.

This is why we need supercomputers to do high resolution weather simulations.

Yep. Any "open distributed alternative" will fall flat because what makes the mother of all social networking site useful, is that everybody frickin' uses it. You could delete your account in protest and start up OpenFrobnitzBook or whatever and have fun updating your status to the other pathetic losers who also deleted their facebook accounts out of protest.

Two easy facebook rules:

1. Tweak your privacy options to your liking
2. Before you post, pretend your future (or current) employer is reading

This will assist you in deciding whether it's a good idea to post those hilarious drunken half-naked pictures of you groping that dude dressed up in a Grimace costume.

Yes, they're great, I have one running Voyage Linux (stripped down Debian).

But Alix doesn't have gigabit ethernet, which sucks. Also, Linux has major problems with wireless G (google stuck beacon) so I'm hesitant to try the same approach with N.