In my recent posts I shared some first hand experience of parallel computing using OpenMP. While OpenMP is supported by many programming languages, there are still a few does not. So here I am sharing another approach to create a parallel computing job.

The utility I will use is called “ParaFly”. There are some information you can read here. Basically, ParaFly can be used to run a list of command simultaneously. This approach will be particularly useful for some types of jobs in which tasks are independent with each other (such as for loop) but take a long time to run.

In my case, I was using the IDL library to process a huge amount to spatial datasets. I will use this job as an example to show how it is done.

Organically, I have to call a routine: PRO project48, extension_file = ef, $filename_mapinfo,$ missing_value, $o_pixel_size,$ prefix_in, $prefix_out = po,$ workspace_in, $workspace_out,$ year_end, $year_start to re-project a list of raster image files from 1980 to 2015. IDL is known for inefficient in for loop just like MATLAB. And it is not easy to parallel IDL on a Linux HPC. You can use C/C++ to call IDL with OpenMP enabled if possible, but then you have to write some additional program to do the work. You can also use GDAL library to write a projection function then you can use OpenMP freely, but that certainly requires some efforts. However, with ParaFly, we can do the work within a few minutes if you are lucky. First, we need to add an additional routine to call the above routine, but this new routine should accept one parameter, which is time(year), because all the other will remain the same. Such as: ;- PRO project48_tmax, year COMPILE_OPT IDL2 year_start = year year_end = year ;;some other lines are remove here project48, extension_file = file_extension,$ filename_mapinfo, $missing_value,$ o_pixel_size, $prefix_in,$ workspace_in, $workspace_out,$ year_end,$year_start PRINT, ‘Finished!’ END Then the routine is wrapped and ready for ParaFly. You may want to write another wrapper to generate the ParaFly file, such as: PRO prepare_parafly_files COMPILE_OPT IDL2 year_start = 1980 year_end = 2015 ;;some other lines are remove here FOR year = year_start, year_end, 1 DO BEGIN year_str = STRING(year, format = ‘(i04)’) str = ‘idl -e ‘+ ‘”’ +’project48_tmax, ‘$ + year_str + ‘”’ PRINTF, lun, str ENDFOR FREE_LUN, lun END

Then work should be done. Theoretically, you can request the whole node with all cores in one job, and then gain speed the number of core faster. For example, if I request 10 cores, then the program will improve to 10 time faster.