Gordon-Simons User Guide

After March 2017, the SDSC Gordon-Simons cluster is no longer an NSF-allocated resource.

Technical Summary

Gordon is a dedicated data-intensive supercompuer designed by Appro and SDSC consisting of 1024 compute nodes and 64 I/O nodes. Each compute node contains two 8-core 2.6 GHz Intel EM64T Xeon E5 (Sandy Bridge) processors and 64 GB of DDR3-1333 memory. The I/O nodes each contain two 6-core 2.67 GHz Intel X5650 (Westmere) processors, 48 GB of DDR3-1333 memory, and sixteen 300 GB Intel 710 solid state drives. The network topology is a 4x4x4 3D torus with adjacent switches connected by three 4x QDR InfiniBand links (120 Gb/s). Compute nodes (16 per switch) and I/O nodes (1 per switch) are connected to the switches by 4x QDR (40 Gb/s). The theoretical peak performance of Gordon is 341 TFlop/s.

Technical Details

Systems Software Environment

• When you login to gordon.sdsc.edu, you will be assigned one of the two login nodes gordon-ln[1-2].sdsc.edu. These nodes are identical in both architecture and software environment.Users can directly access one of the two nodes directly if they see poor performance
• When using screen or tmux be aware of the login node on which the session was started.  When you try to reconnect to the old session be sure to use the same login node on which you started the original screen or tmux session.

Modules

The Environment Modules package provides for dynamic modification of your shell environment. Module commands set, change, or delete environment variables, typically in support of a particular application. They also let the user choose between different versions of the same software or different combinations of related codes.

For example, if the Intel module and mvapich2_ib module are loaded and the user compiles with mpif90, the generated code is compiled with the Intel Fortran 90 compiler and linked with the mvapich2_ib MPI libraries.

Several modules that determine the default Gordon environment are loaded at login time. These include the MVAPICH2 implementation of the MPI library and the Intel compilers. We strongly suggest that you use this combination whenever possible to get the best performance.

Notes and Hints

Making modification to your .bashrc or .bash_profile may cause unexpected behaviour with respect to modules.  Loading modules sets environmental variables and dynamic library paths.  If you modify your path in .bash or .bash_profile you may have unexpected resultes becasue you may overwrite paths that are set by the modules.

Useful Modules Commands

Here are some common module commands and their descriptions:

Loading and unloading modules

You must remove some modules before loading others.

Some modules depend on others, so they may be loaded or unloaded as a consequence of another module command. For example, if intel and mvapich2_ib are both loaded, running the command module unload intel will automatically unload mvapich2_ib. Subsequently issuing the module load intel command does not automatically reload mvapich2_ib.

If you find yourself regularly using a set of module commands, you may want to add these to your configuration files (.bashrc for bash users, .cshrc for C shell users). Complete documentation is available in the module(1) and modulefile(4) manpages.

Module: command not found

The error message module: command not found is sometimes encountered when switching from one shell to another or attempting to run the module command from within a shell script or batch job.  The reason that the module command may not be inherited as expected is that it is defined as a function for your login shell. If you encounter this error execute the following from the command line (interactive shells) or add to your shell script (including Slurm batch scripts)

source /etc/profile.d/modules.sh 

Compiling

Gordon provides the Intel and GNU compilers along with multiple MPI implementations (MVAPICH2, MPICH2, OpenMPI). Most applications will achieve the best performance on Gordon using the Intel compilers and MVAPICH2, and the majority of libraries installed on Gordon have been built using this combination. Although other compilers and MPI implementations are available, we suggest using these only for compatibility purposes.

All compilers now support the Advanced Vector Extensions (AVX). Using AVX, up to eight floating point operations can be executed per cycle per core, potentially doubling the performance relative to non-AVX processors running at the same clock speed. Note that AVX support is not enabled by default and compiler flags must be set as described below.

Using the Intel compilers (Default/Suggested)

The Intel compilers and the MVAPICH2 MPI implementation will be loaded by default. If you have modified your environment, you can reload by executing the following commands at the Linux prompt or placing in your startup file (~/.cshrc or ~/.bashrc)

module purge
module load intel mvapich2_ib

For AVX support, compile with the -xHOST option. Note that -xHOST alone does not enable aggressive optimization, so compilation with -O3 is also suggested. The -fast flag invokes -xHOST, but should be avoided since it also turns on interprocedural optimization (-ipo), which may cause problems in some instances.

Intel MKL libraries are available as part of the "intel" module on Gordon. Once this module is loaded, the environment variable MKL_ROOT points to the location of the mkl libraries. The MKL link advisor can be used to ascertain the link line (Note:  If you use MKL link advisor to get a link line used in your makefile or configuration, you will need to either modify the env variable name or change the link line explicitly from MKLROOT(as it is set in the link advisor) to MKL_ROOT as shown below.   

For example to compile a C program statically linking 64 bit scalapack libraries on Gordon:

module unload mvapich2_ib
module unload pgi
module load intel
module load mvapich2_ib
mpicc -o pdpttr.exe pdpttr.c \
    -I$MKL_ROOT/include ${MKL_ROOT}/lib/intel64/libmkl_scalapack_lp64.a \
    -Wl,--start-group ${MKL_ROOT}/lib/intel64/libmkl_intel_lp64.a \
    ${MKL_ROOT}/lib/intel64/libmkl_core.a ${MKL_ROOT}/lib/intel64/libmkl_sequential.a \
    -Wl,--end-group ${MKL_ROOT}/lib/intel64/libmkl_blacs_intelmpi_lp64.a -lpthread -lm

For more information on the Intel compilers: [ifort | icc | icpc] -help

Note for C/C++ users:  The compiler warning - "feupdateenv is not implemented and will always fail", can safely be ignored by most users. By default, the Intel C/C++ compilers only link against Intel's optimized version of the C standard math library (libmf). The error stems from the fact that several of the newer C99 library functions related to floating point rounding and exception handling have not been implemented.

Using the GNU compilers

The GNU compilers can be loaded by executing the following commands at the Linux prompt or placing in your startup files (~/.cshrc or ~/.bashrc)

module purge
module load gnu openmpi

For AVX support, compile with -mavx.

For more information on the GNU compilers: man [gfortran | gcc | g++]

Notes and Hints

• The mpif90, mpicc, and mpicxx commands are actually wrappers that call the appropriate serial compilers and load the correct MPI libraries. While the same names are used for the Intel and GNU compilers, keep in mind that these are completely independent scripts.
• If you use the GNU compiler or switch between compilers for different applications, make sure that you load the appropriate modules before running your executables.
• When building OpenMP applications and moving between different compilers, one of the most common errors is to use the wrong flag to enable handling of OpenMP directives. Note that Intel and GNU compilers use the -openmp and -fopenmp flags, respectively.
• Explicitly set the optimization level in your makefiles or compilation scripts. Most well written codes can safely use the highest optimization level (-O3), but many compilers set lower default levels (e.g. GNU compilers use the default -O0, which turns off all optimizations).

Running Jobs on Compute Nodes

Gordon uses the Simple Linux Utility for Resource Management (Slurm)  environment to manage user jobs.  Whether you run in batch mode or interactively, you will access the compute nodes using the sbatch, or srun, command as described below.  Remember that computationally intensive jobs should be run only on the compute nodes and not the login nodes.

Gordon Partitions

Gordon has the following partitions available:

Requesting interactive resources using srun

You can request an interactive session using the srun command as follows:

[user@gordon-ln1]$ srun --pty --nodes=1 --ntasks-per-node=16 -p general -t 00:30:00 --wait 0 /bin/bash

Submitting Jobs Using sbatch

Jobs can be submitted to the sbatch partitions using the sbatch command as follows:

[user@gordon-ln1]$ sbatch jobscriptfile

where jobscriptfile is the name of a UNIX format file containing special statements (corresponding to sbatch options), resource specifications and shell commands. Several example Slurm scripts are given below:

Basic MPI Job

#!/bin/bash
#SBATCH --job-name="hellompi"
#SBATCH --output="hellompi.%j.%N.out"
#SBATCH --partition=general
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=16
#SBATCH --export=ALL
#SBATCH -t 01:30:00

#This job runs with 2 nodes, 16 cores per node for a total of 32 cores.
#ibrun in verbose mode will give binding detail

srun  -n 32 --mpi=pmi2  ../hello_mpi 

Basic OpenMP Job

#!/bin/bash
#SBATCH --job-name="hello_openmp"
#SBATCH --output="hello_openmp.%j.%N.out"
#SBATCH --partition=general
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=16
#SBATCH --export=ALL
#SBATCH -t 01:30:00

#SET the number of openmp threads
export OMP_NUM_THREADS=16

./hello_openmp 

Hybrid MPI-OpenMP Job

#!/bin/bash
#SBATCH --job-name="hellohybrid"
#SBATCH --output="hellohybrid.%j.%N.out"
#SBATCH --partition=general
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=16
#SBATCH --export=ALL
#SBATCH -t 01:30:00

#This job runs with 2 nodes, 16 cores per node for a total of 32 cores.
# We use 8 MPI tasks and 4 OpenMP threads per MPI task

export OMP_NUM_THREADS=4
srun  -n 8 -cpus=per-task=4 --mpi=pmi2 ./hello_hybrid 

Basic mpirun_rsh Job

#!/bin/bash
#SBATCH --job-name="hellompirunrsh"
#SBATCH --output="hellompirunrsh.%j.%N.out"
#SBATCH --partition=general
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=16
#SBATCH --export=ALL
#SBATCH -t 01:30:00

#Generate a hostfile from the slurm node list
export SLURM_NODEFILE=`generate_pbs_nodefile`

#Run the job using mpirun_rsh
mpirun_rsh -hostfile $SLURM_NODEFILE -np 32 ../hello_mpi

Job Dependencies

There are several scenarios (e.g. splitting long running jobs, workflows) where users may require jobs with dependencies on successful completions of other jobs. In such cases, Slurm's --dependency option can be used. The syntax is as follows:

[user@gordon-ln1 ~]$ sbatch --dependency=afterok:jobid jobscriptfile