These are the guidelines for running computations on the department computer system. This page contains:
If you have access to a fast stand-alone PC in your office, we encourage running your computations on this computer. In addition, you can access the following computers with SSH:
| Host name | Operating system | CPUs | Memory | Available compilers |
|---|---|---|---|---|
| syvert | Linux (Ubuntu 7.10) | 8 Intel CPUs (2×Quad-core Xeon 3.0 GHz) | 16 GB | GNU Fortran/C/C++ |
| schwarz | FreeBSD 6.2-RELEASE | 2 Intel CPUs (2×Xeon 3.06 GHz) | 4 GB | GNU Fortran/C/C++ |
| lie | Solaris 9 | 12 UltraSPARC CPUs (6×UltraSPARC IV 1.2 GHz) | 24 GB | Sun Studio 10 Fortran/C/C++ and GNU Fortran/C/C++ |
All computations running on syvert, schwarz and lie must be started by adding the special command compute before the command that starts the computation. (You may also use the special command beregning, these are equivalent. The example below uses beregning).
Examples:
lie:~$ beregning matlab lie:~$ beregning ./a.out lie:~$ beregning matlab -nojvm mysim.m lie:~$ beregning ./ns -N 8 -T 10 init.dat > sim.out
and so on. The compute/beregning command makes sure that your computation is run with the right priority, so that you don't have to worry about using more than your share of CPU.
To make your computations run as fast as possible:
The following compilers are available:
| Host | Compiler | Command |
|---|---|---|
| syvert | GNU C compiler 4.1 GNU C compiler 4.2 GNU C++ compiler 4.1 GNU C++ compiler 4.2 GNU Fortran 4.2 | gcc -O2 gcc-4.2 -O3 -march=native g++ -O2 g++-4.2 -O3 -march=native gfortran -O3 -march=native |
| schwarz | GNU C compiler 3.4 GNU C compiler 4.2 GNU C++ compiler 3.4 GNU C++ compiler 4.2 GNU Fortran 3.4 | gcc -O2 gcc42 -O3 -march=native g++ -O2 g++42 -O3 -march=native f77 -O2 |
| lie | Sun Studio 10 C Sun Studio 10 C++ Sun Studio 10 Fortran GNU C compiler 3.4 GNU C++ compiler 3.4 GNU Fortran 3.4 | cc -fast CC -fast f77 -fast, f90 -fast, f95 -fast gcc -O2 g++ -O2 g77 -O2 |
/global/work/<username> (replace <username> with your login name). This directory is accessible from all our Unix computers. It is also accessible from Windows as \\mamba.math.ntnu.no\work\<username>. Some hosts also have a scratch directory named /work that can be used for this purpose. While /work is not shared (not accessible from Windows or from other Unix hosts), it is noticeably faster than /global/work, so for disk-intensive processes, /work is preferred./work or /global/work for that.