Python is used to glue all the lower level stuff together. If you are iterating over large arrays in python you are doing something wrong, but if you are using python to glue C/Fortran molecules together then it starts to look much better.
Our aircraft carriers are longer then yours!
On a more serious note the largest calculation that I can find (in terms of # of cores utilized) was a fluid dynamics calculation with a million cores on Sequoia. From my own experience we usually utilize 4-100 cores for throughput over the speed of a single job- if it takes a month to do then so be it.
If they can do this for helium it would be very, very interesting if electron correlation effects could be seen. I am not sure if their current resolution would be able to show such minute effects.
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Python is used to glue all the lower level stuff together. If you are iterating over large arrays in python you are doing something wrong, but if you are using python to glue C/Fortran molecules together then it starts to look much better.
That why I usually prefer the BEST competition. Very similar events, but BEST puts everyone on the same playing field. http://best.eng.auburn.edu/wor... http://en.wikipedia.org/wiki/B...
Something to actually use.
Out of curiosity how many cores do you use on a typical job?
Our aircraft carriers are longer then yours! On a more serious note the largest calculation that I can find (in terms of # of cores utilized) was a fluid dynamics calculation with a million cores on Sequoia. From my own experience we usually utilize 4-100 cores for throughput over the speed of a single job- if it takes a month to do then so be it.
Yea! Transistors have never bigger then 10 micrometers.
If they can do this for helium it would be very, very interesting if electron correlation effects could be seen. I am not sure if their current resolution would be able to show such minute effects.