From: bangerth Date: Thu, 30 Jan 2014 17:23:49 +0000 (+0000) Subject: Add a few statements on running stuff in parallel with MPI. X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=59b8887f48357c660d9351711758d8ed32ce26d6;p=dealii-svn.git Add a few statements on running stuff in parallel with MPI. git-svn-id: https://svn.dealii.org/trunk@32347 0785d39b-7218-0410-832d-ea1e28bc413d --- diff --git a/deal.II/examples/step-17/doc/results.dox b/deal.II/examples/step-17/doc/results.dox index 9720ab3172..cb545b7eee 100644 --- a/deal.II/examples/step-17/doc/results.dox +++ b/deal.II/examples/step-17/doc/results.dox @@ -1,18 +1,26 @@

Results

-If the program above is compiled and run on a single processor machine, it -should generate results that are very similar to those that we already got -with step-8. However, it becomes more interesting if we run it on a cluster of -computers. Most clusters have some kind of scheduling system, all of which -have different calling syntaxes - on my system, I have to use the command -bsub with a whole host of options to run a job in parallel - so -that the exact command line syntax varies. If you have found out how to run a -job on your system, you should get output like this for a job on 8 processors, -and with a few more refinement cycles than in the code above (these -results were generated in 2004 with older versions of deal.II and a -version of METIS that generated different partitionings; consequently, -the numbers you get today are slightly different): +If the program above is compiled and run on a single processor +machine, it should generate results that are very similar to those +that we already got with step-8. However, it becomes more interesting +if we run it on a multicore machine or a cluster of computers. The +most basic way to run MPI programs is using a command line like +@code + mpirun -np 32 ./step-17 +@endcode +to run the step-17 executable with 32 processors. + +The command line above is the appropriate way of starting the program +on a multicore machine when using MPI for parallelization. On the +other hand, most clusters are shared resources and have some kind of +scheduling system that distributes jobs onto available processors. All +of these scheduling systems have their own calling syntax - on my system, I have to use the command +qsub with a whole host of options to run a job in parallel - so +that the exact command line syntax varies. + +Whether directly or through a scheduler, if you run this program on 8 +processors, you should get output like the following: @code Cycle 0: Number of active cells: 64 @@ -84,8 +92,10 @@ Cycle 16: 471186+470686+475694) Solver converged in 2251 iterations. @endcode - - +(This run uses a few more refinement cycles than the code available in +the examples/ directory. The run also used a version of METIS from +2004 that generated different partitionings; consequently, +the numbers you get today are slightly different.) As can be seen, we can easily get to almost four million unknowns. In fact, the code's runtime with 8 processes was less than 7 minutes up to (and including)