{"id":1087,"date":"2015-11-27T10:18:07","date_gmt":"2015-11-27T15:18:07","guid":{"rendered":"http:\/\/10.0.0.102:8080\/?p=1087"},"modified":"2024-04-16T09:59:22","modified_gmt":"2024-04-16T13:59:22","slug":"ligghts","status":"publish","type":"post","link":"https:\/\/knowledgebasev.kinsta.cloud\/?p=1087","title":{"rendered":"LIGGGHTS"},"content":{"rendered":"

LIGGGHTS\u00ae is an Open Source Discrete Element Method Particle Simulation Software provided by\u00a0CFDEM\u00ae project<\/a>. This article demonstrates the basic steps to run and visualize a simple LIGGGHTS\u00ae simulation using Sabalcore Computing’s HPC On-Demand service. Before proceeding with this demo, you should understand the basics submitting\u00a0batch and interactive<\/a>\u00a0jobs and using\u00a0modules<\/a>\u00a0at Sabalcore.<\/p>\n

First, run the\u00a0module help liggghts<\/strong>\u00a0command to see information about the latest installed version of LIGGGHTS\u00ae:<\/p>\n

$ module help liggghts\r\n----------- Module Specific Help for 'liggghts\/3.3.0' -------------\r\n Name: liggghts\r\n Version: 3.3.0\r\n Installed: Wed Nov 25 16:35:48 EST 2015\r\n\r\nAn example is available for liggghts. To use the example, \r\nrun the following commands:\r\n\r\ncp -a \/uls\/6\/liggghts-3.3.0\/example\/chute_wear .\r\ncd chute_wear\r\nqsub liggghts.pbs<\/pre>\n
In this case we have version 3.3.0 available. Also, you can see some information about running the example.<\/p>\n
The next step is to copy the example to your home directory with the command:<\/p>\n
cp -a \/uls\/6\/liggghts-3.3.0\/example\/chute_wear .<\/pre>\n
Now cd to the chute_wear directory and take a look at the liggghts.pbs job script:<\/p>\n
#PBS -l nodes=1:ppn=16:cobalt\r\n#PBS -l nodes+=1:ppn=24:copper\r\n#PBS -l nodes++=1:ppn=12:red\r\n\r\nmodule load liggghts\r\n\r\ncd $PBS_O_WORKDIR\r\nmpirun liggghts < in.chute_wear<\/pre>\n
As you can see, this job is setup to run on 16 cores on the\u00a0cobalt<\/em>\u00a0or 24 cores on copper<\/em> or 12 cores on the\u00a0bronze<\/em>\u00a0cluster. This is a basic job script which can be modified to meet your specific needs for your LIGGGHTS\u00ae jobs.<\/p>\n
Now submit the job to the clusters using qsub:<\/p>\n
qsub liggghts.pbs<\/pre>\n
Once the job has been submitted, you can monitor it with the\u00a0qstat<\/em>\u00a0command. After the job has completed, it’s time to visualize the results using Paraview via a\u00a0Remote Graphics<\/a>\u00a0session. To do this, you need to submit an interactive job using either of the following commands:<\/p>\n
qsub -I -l nodes=1:graphics:ppn=8:gpn=1\r\n     -- OR --\r\nqsub -I -l nodes=1:ppn=1<\/pre>\n
The first option will use one of the graphics nodes and will utilize a GPU to preform hardware accelerated 3D rendering. You should use this option if you have a very large\/complex 3D object to visualize. The second option will use software rendering and is preferred for simple or small 3D images. For this demo you can use the second option.<\/p>\n
Once the interactive job has started, you will be logged into one of the compute nodes. At this point you need to load the\u00a0liggghts<\/em>\u00a0and\u00a0paraview<\/em>\u00a0modules:<\/p>\n
[09:47 user@n716021 ~]$ module load liggghts\r\n[09:47 user@n716021 ~]$ module load paraview\r\n[rg3d]: This node does not support hw *accelerated* 3D graphics.\r\n[rg3d]: Using software level rendering.<\/pre>\n
Because we are not on a\u00a0graphics<\/em>\u00a0node with a GPU, we get a warning regarding the missing GPU. You can ignore this warning since we are going to visualize a rather simple model.<\/p>\n
Next,\u00a0cd<\/em>\u00a0to the ‘post’ directory under the ‘chute_wear’ directory and run the lpp command (LIGGGHTS\u00ae post-processing) to generate VTK data for use with Paraview:<\/p>\n
[09:55 user@n716021 post]$ cd ~\/chute_wear\/post\r\n[09:55 user@n716021 post]$ lpp dump*.chute\r\nstarting LIGGGHTS memory optimized parallel post processing\r\nchunksize: 8 --> 8 files are processed per chunk. If you run out of memory reduce chunksize.\r\nWorking with 16 processes...\r\ncalculating chunks 1 - 16 of 63\r\ncalculating chunks 17 - 32 of 63\r\ncalculating chunks 33 - 48 of 63\r\ncalculating chunks 49 - 63 of 63\r\nwrote 500 granular snapshots in VTK format\r\ntime needed: 12.5661559105 sec<\/pre>\n
Now start up Paraview with the\u00a0paraview<\/em>\u00a0command and open the ‘*.vtk’ files and setup your visualization. You should see something similar to this:<\/p>\n
\"liggghts_chute_wear\"<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
LIGGGHTS\u00ae is an Open Source Discrete Element Method Particle Simulation Software provided by\u00a0CFDEM\u00ae project. This article demonstrates the basic steps to run and visualize a simple LIGGGHTS\u00ae simulation using Sabalcore Computing’s HPC On-Demand service. Before proceeding with this demo, you should understand the basics submitting\u00a0batch and interactive\u00a0jobs and using\u00a0modules\u00a0at Sabalcore. First, run the\u00a0module help liggghts\u00a0command […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[142,92],"class_list":["post-1087","post","type-post","status-publish","format-standard","hentry","category-software-specific-guides","tag-liggghts","tag-paraview"],"_links":{"self":[{"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=\/wp\/v2\/posts\/1087","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1087"}],"version-history":[{"count":8,"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=\/wp\/v2\/posts\/1087\/revisions"}],"predecessor-version":[{"id":2017,"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=\/wp\/v2\/posts\/1087\/revisions\/2017"}],"wp:attachment":[{"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1087"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1087"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/knowledgebasev.kinsta.cloud\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1087"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}