11–20 of 55 posts
At Nerdalize we're building a cloud that's specifally build for high performance scientific compute: http://www.nerdalize.com/cloud/
This site is going down the drain. More and more like Slashdot and others. I'll only post useless comments any more, anything else is a waste of effort. The only way to achieve change is to make things WORSE. New mission: I'll slowly help lower the quality of this "discussion" with two many angry know-nothing teenagers even more.
Looks like a good collection of important topics. The tutorials feel a bit 2005 to me. GNUplot and svn? In my scientific universe it's all matplotlib and git these days. Maybe I'm unique.
Gnuplot is still used quite a lot in my area. You need to work more to make something aesthetically pleasing, but it's generally a better fit to plotting large amounts of data coming from another code. I've also been quite badly burnt by Matplotlib scripts no longer producing the same plot with changes in the library. Gnuplot version 5+ is nicer to use and has some pretty powerful features. This blog has been a good…
SVN also has the important advantage of being relatively easy to pick up by someone who's not a programmer. It would not be my first choice for a version control system now that we have Mercurial and git (frankly, it wasn't not even back when our only affordable alternatives were CVS and RCS), but it's very easy to teach it.
Earlier quoted context omitted.
You might want to run a spell check on that page, I just saw "comprimise" in the most prominent sentence. Also, white text on sky background with white patches (sun, clouds) has unreadable portions.
Thanks for the comment, we fixed the typo. Any ideas on the content of the website are also very welcome.
At Nerdalize we're building a cloud that's specifally build for high performance scientific compute: http://www.nerdalize.com/cloud/
At Nerdalize we're building a cloud that's specifally build for high performance scientific compute: http://www.nerdalize.com/cloud/
I never got into high performance scientific computing, but I believe the stuff that was done in my department at university was all MPI based and required very high interconnect speeds (like with Infiniband). It looks like your offering is much more standard, what's the thinking there, or am I just wrong/out of date?
If you look at the BOINC project those are basically all problems of this kind. Folding proteins like folding@home does for example. The description of a protein is fairly small, a couple megabyte max. However it takes a long time to simulate the behaviour, since chemistry is a messy probabilistic process with lots of back and forth. Nature does this on trillions of proteins at the same time within nanoseconds, and while we cannot reasonably increase the simulation speed of an individual protein, we can at least simulate as many proteins at once as possible.
Looks like a good collection of important topics. The tutorials feel a bit 2005 to me. GNUplot and svn? In my scientific universe it's all matplotlib and git these days. Maybe I'm unique.
To me, "gnuplot or matplotlib" is a little beside the point - if we're using one of those it's for something quick 'n dirty, or for a relatively simple plot of summary data.
Looks like a good collection of important topics. The tutorials feel a bit 2005 to me. GNUplot and svn? In my scientific universe it's all matplotlib and git these days. Maybe I'm unique.
