I have a bit of experience programming and I am pretty sure I get my parts of the code pretty well optimized. I made sure that in the loop I have only the stuff needed and I'm loading all the stuff before.
The biggest bottleneck is happening because I'm unpacking grib files to csv files using Degrib in command line. That operation is usually around half an hour using no more than 50% of the processor but it maxes out the memory usage and it definitely is hard drive intensive as it ends up writing over 4 GB of data. I have noticed also that on a lower spec AMD desktop this runs faster than on my P4 Intel Laptop, my guess being that the laptop hdd is 5400 rpm and the desktop is 7200 rpm. Next step is to take all those csv files and make images from them. For this one I haven't dug too deep to see what is happening but it seems to be the other way, using the cpu a lot more while keeping the memory usage high too. Thanks, Anton -- View this message in context: http://www.nabble.com/Computer-specs-for-fast-matplotlib-and-basemap-processing-tp22956400p22959409.html Sent from the matplotlib - users mailing list archive at Nabble.com. ------------------------------------------------------------------------------ This SF.net email is sponsored by: High Quality Requirements in a Collaborative Environment. Download a free trial of Rational Requirements Composer Now! http://p.sf.net/sfu/www-ibm-com _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
