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AMBER

Software Description: 

AMBER. Assisted Model Building with Energy Refinement. AMBER refers to two things: a molecular mechanical force field for the simulation of biomolecules (which is in general use in a variety of simulation programs)- and a package of molecular simulation programs which includes source code and demos.

Software Support Level: 
Secondary Support
Software Access Level: 
Open Access
Itasca Documentation: 
Amber 11 is available on Itasca. Calling the sander.MPI binary on more than one node (8 cores) requires the amber module to be loaded in your .bashrc file. If you are running pmemd.MPI this step is not necessary. A sample job script is below.
#!/bin/bash -l
#PBS -l walltime=8:00:00,pmem=1000mb,nodes=8:ppn=8
#PBS -m abe

module load amber/11

cd $PBS_O_WORKDIR

mpirun -np 64 -hostfile $PBS_NODEFILE `which pmemd.MPI` \
  -O -i mdin -c eq200.x -o cellulose.sander.log

Additional Documentation

PBS Example: 

An example PBS script for submitting AMBER jobs to the queue is shown below.

#!/bin/bash -l 
#PBS -l walltime=24:00:00,mem=16gb,nodes=2:ppn=8 
#PBS -m abe 

module load amber 

cd $PBS_O_WORKDIR 

mpirun sander.MPI -O -i AMP2md39.in -o AMP2md39.out -p \
  AMP2_wat.prmtop -c AMP2md38.rst -r AMP2md39.rst -x \
  AMP2md39.mdcrd
Software Interactive/GUI: 
No
General Linux Documentation: 

To run this software interactively in a Linux environment run the command:

module avail amber

and choose the most recent version of the software applicable to your research. The exact name of the module will vary from machine to machine, and over time with new updates so be sure to study the list printed with the 'module avail' command demonstrated above. For example,

module load amber/11
The amber module requires and will automatically load several other modules. Pay attention to any error messages or warnings that result from loading the module as conflicts with other packages already loaded in your environment are a common source of error. An example submission script is below. Note that the #PBS lines need to be tuned for each cluster's policies. You may not need to run short jobs through the queue, so the program can be used interactively by loading the module and running the executable directly at the command prompt.
#!/bin/bash -l 
#PBS -l walltime=24:00:00,mem=16gb,nodes=2:ppn=8 
#PBS -m abe 

module load amber 

cd $PBS_O_WORKDIR 

mpirun sander.MPI -O -i AMP2md39.in -o AMP2md39.out -p \
  AMP2_wat.prmtop -c AMP2md38.rst -r AMP2md39.rst -x \
  AMP2md39.mdcrd

Additional Documentation

TURBOMOLE

Software Support Level: 
Secondary Support
Software Description: 

TURBOMOLE is a program package for ab initio electronic structure calculations. It can carry out HF, DFT, and MP2 calculations for ground-state properties. It can also perform CIS, CIS(D) and CC2 calculations for excited-state properties.

Software Access Level: 
Open Access
PBS Example: 
#!/bin/bash -l

#PBS -l nodes=2:ppn=4
#PBS -l walltime=1:00:00
#PBS -l mem=4000mb

module load turbomole

cd $PBS_O_WORKDIR

## set locale to C

unset LANG
unset LC_CTYPE

# set stack size limit to unlimited:

ulimit -s unlimited

# Count the number of nodes

PBS_L_NODENUMBER=`wc -l < $PBS_NODEFILE`

# Check if this is a parallel job

if [ $PBS_L_NODENUMBER -gt 1 ]; then

##### Parallel job

# Set environment variables for a MPI job

    export PARA_ARCH=MPI
    export PATH="${TURBODIR}/bin/`sysname`:${PATH}"
    export PARNODES=`expr $PBS_L_NODENUMBER`

else

##### Sequentiel job

# set the PATH for Turbomole calculations

    export PATH="${TURBODIR}/bin/`sysname`:${PATH}"

fi

tmole
Software Categories: 
Software Interactive/GUI: 
No
General Linux Documentation: 

Below is an example of a Turbomole input file named turbo.in (file must be named turbo.in for this to work), and a PBS script to submit it to the queue. 

Input file:

%title

DFT geometry optimization for water

%method

GEOMY :: b-p/SVP

%charge

0

%coord

 0.00000000000000      0.00000000000000     -0.69098999073900     o

-1.46580510295113      0.00000000000000      0.34549499536950     h

 1.46580510295113      0.00000000000000      0.34549499536950     h

%end

Allinea MAP

Software Support Level: 
Secondary Support
Software Description: 

Allinea MAPis a profiler for serial and parallel applications written in C, C++, FORTRAN 77, Fortran 90. It supports multiple parallel programming paradigms including MPI, and OpenMP.

Software Access Level: 
Open Access
Software Categories: 
Software Interactive/GUI: 
No
General Linux Documentation: 
To run this software in a Linux environment run the commands:
module load allinea-tools intel/12.0 ompi/1.5.4/intel
map

To profile your application, you need to build it with the MAP libraries, for example:

module load allinea-tools intel/12.0 ompi/1.5.4/intel
C: mpicc -g -O3 your.c -lmap-sampler
C++: mpicxx -g -O3 your.c -lmap-sampler
FORTRAN: mpif90 -g -O3 your.c -lmap-sampler

On the login nodes, you can use MAP only up to the number of cores available. For an MPI job to run across nodes, one need run MAP interactively through a queue by " qsub -I -X -q batch ". Here is the procedure for profiling a MPI job to run over 2 nodes:

qsub -I -X -l nodes=2:ppn=8,mem=20gb,walltime=1:00:00
cd your_work_directory
module load allinea-tools intel/12.0 ompi/1.5.4/intel
map

For Platform MPI, the following commands are used for profiling an MPI application:

module load intel pmpi/8.2.0/intel allinea-tools
export LD_LIBRARY_PATH=/opt/platform_mpi-8.02.00.00-20121216r/MPICH1.2/lib/linux_amd64:$LD_LIBRARY_PATH
export MPICC=mpicc.mpich
mpif90.mpich -g -O3 mpi_hello.f
map -profile -n 4 ./a.out

For Intel MPI, please try the following

module load intel impi/intel allinea-tools
map -n 4 -profile -mpiargs "-r ssh -f nodelist" ./a.out

Where nodelist is a file containing the name of nodes assigned for running the job

node1155

node1156

node1154

node1157

More working examples for building scalar and parallel applications (with a variety of versions of MPI) are in

/soft/allinea-tools/4.1-32296/examples

MEMS Proportional Pneumatic Valve

Abstract: 

MEMS Proportional Pneumatic Valve

This project involves designing a new type of generic pneumatic valve based on micro-electrical-mechanical-systems (MEMS) technology. The valve utilizes an array of micro-actuators positioned over a matching array of micro-orifices. Several benefits are realized by using this scheme instead of a single large actuator acting on a single large orifice. The three most notable are very low actuation power requirements, very fast response and potentially very low cost. The potential cost benefits are realized by exploiting MEMS batch fabrication technologies. MSI resources are utilized to do computational mechanics flow modeling for the valve.

A bibliography of this group’s publications is attached.

Return to this PI's main page.

 

Group name: 
chasetr
Attachment: 

QChem

Software Description: 

Q-Chem is a comprehensive ab initio quantum chemistry package. Its capabilities range from the highest performance DFT/HF calculations to high level post-HF correlation methods.

The QChem module is available on the Itasca and Cascade clusters.

 

Software Support Level: 
Secondary Support
Software Access Level: 
Open Access
Itasca Documentation: 

To run the application interactively in the Linux environment run the commands:

module load qchem
qchem water.in

Other versions of qchem are available. The "serial" type installations support single threaded and multi-threaded (OpenMP) execution. The "parallel" type installations support MPI execution (via a QChem-internal version of MPICH). The naming scheme for each type follows: 

qchem/4.1_parallel
qchem/4.1_serial
qchem/parallel
qchem/serial (default)

To run QChem in multi-threaded (OpenMP) mode, specify the number of threads with "-nt": 

qchem -nt 4 DFT_glutamine.in output.out
PBS Example: 

The following example demonstrates how to run Q-Chem with 16 MPI processes:

#!/bin/bash -l

#PBS -l walltime=01:00:00,mem=21gb,nodes=2:ppn=8
#PBS -m abe

module load qchem/4.1_parallel

cat $PBS_NODEFILE               

# Uncomment these lines to get 1 proc per node (the ppn=8 must
# remain above)
#cat $PBS_NODEFILE | sort -u > $PBS_O_WORKDIR/machinefile
#export PBS_NODEFILE=$PBS_O_WORKDIR/machinefile

NN=`cat $PBS_NODEFILE | wc -l`
echo "Launching job for NN=$NN processes"

cd $PBS_O_WORKDIR

# Sample input files are available with each module
cp /soft/qchem/3.2_parallel/samples/DFT_glutamine.in .

qchem -pbs -np $NN $PBS_O_WORKDIR/DFT_glutamine.in \

$PBS_O_WORKDIR/output.out 
Software Interactive/GUI: 
No

ALLPATHS-LG

Software Support Level: 
Secondary Support
Software Description: 

ALLPATHS-LG is a whole-genome shotgun assembler that can generate high-quality genome assemblies using short reads (~100bp) such as those produced by the new generation of sequencers. The significant difference between ALLPATHS and traditional assemblers such as Arachne is that ALLPATHS assemblies are not necessarily linear, but instead are presented in the form of a graph. This graph representation retains ambiguities, such as those arising from polymorphism, uncorrected read errors, and unresolved repeats, thereby providing information that has been absent from previous genome assemblies.

Software Access Level: 
Open Access
PBS Example: 

An example PBS script for submitting ALLPATHS-LG jobs to the queue is shown below.

#PBS -l nodes=1:ppn=8,mem=1gb,walltime=4:00:00
#PBS -m abe
module load allpaths-lg

# Prepare input data
mkdir -p test.genome/data
PrepareAllPathsInput.pl \
DATA_DIR=$PWD/test.genome/data

# Assemble data
RunAllPathsLG \
PRE=$PWD \
DATA_SUBDIR=data \
RUN=run \
REFERENCE_NAME=test.genome
Software Categories: 
Software Interactive/GUI: 
No
General Linux Documentation: 

To run this software interactively in a Linux environment run the commands:

module load allpathslg
PrepareAllPathsInputs.pl DATA_DIR=/path/to/data
RunAllPathsLG PRE=<pre> DATA_SUBDIR=<data> RUN=<ref> REFERENCE_NAME=<ref>

Note:

  • The PrepareAllPathsInputs.pl script requires one parameter, the path to the directory containing the input data.<pre> is the root directory ALLPATHS-LG will use. <data> is the subdirectory containing the input data. <run> is the directory used for assembly pre-processing. <ref> is the organism or reference genome name.

  • ALLPATHS-LG is composed of a number of modules, each of which performs a step in the assembly process.  While each module can be run individually, ALLPATHS-LG provides a module that controls the entire assembly pipeline, called RunAllPathsLG.  In addition, before ALLPATHS-LG can be used, data must be converted using the Perl script PrepareAllPathsInputs.pl.

  • AllPathsLG assembler has specific requirement for the paired-end read libraries.  It requires the paired read to be actually interwinded. 

A more detailed discussion of each of these directories, as well as a list of other command-line arguments, is avaible in the user manual.  Other ALLPATHS-LG utilities may be found in the directory

/soft/allpathslg/VER/bin

where VER is the version of ALLPATHS-LG you are using.

An example PBS script for submitting ALLPATHS-LG jobs to the queue is shown below.

#PBS -l nodes=1:ppn=8,mem=1gb,walltime=4:00:00
#PBS -m abe
module load allpaths-lg

# Prepare input data
mkdir -p test.genome/data
PrepareAllPathsInput.pl \
DATA_DIR=$PWD/test.genome/data

# Assemble data
RunAllPathsLG \
PRE=$PWD \
DATA_SUBDIR=data \
RUN=run \
REFERENCE_NAME=test.genome

Additional Information

Gaussian Graph Estimation and Recommendation System

Abstract: 

Gaussian Graph Estimation and Recommendation System

Multiple graphical models have been widely used to describe structural changes of a network responding to certain experimental conditions, which are expressed in terms of conditional dependence between interacting units. For instance, time-varying functional connectivity in brain image analysis is described by node connectivity over a dynamic network, with each node corresponding to one region of interest. Motivated from network analysis under different experimental conditions, such as gene networks for disparate cancer subtypes, these researchers model structural changes over multiple networks with possible heterogeneities. In particular, they estimate multiple precision matrices describing dependencies among interacting units through maximum penalized likelihood. Of particular interest are homogeneous groups of similar entries across and zero-entries of these matrices, referred to as clustering and sparseness structures, respectively. A non-convex method is proposed to seek a sparse representation for each matrix and identify clusters of the entries across the matrices. An efficient method is developed on the basis of difference convex programming, the augmented Lagrangian method, and the blockwise coordinate descent method, which is scalable to hundreds of graphs of thousands nodes through a simple necessary and sufficient partition rule, which divides nodes into smaller disjoint subproblems excluding zero-coefficients nodes for arbitrary graphs with convex relaxation. Theoretically, a finite-sample error bound is derived for the proposed method to reconstruct the clustering and sparseness structures. This leads to consistent reconstruction of these two structures simultaneously, permitting the number of unknown parameters to be exponential in the sample size, and yielding the optimal performance of the oracle estimator as if the true structures were given a priori. Simulation studies suggest that the method enjoys the benefit of pursuing these two disparate kinds of structures, and compares favorably against its convex counterpart in the accuracy of structure pursuit and parameter estimation.

Return to this PI's main page.

Group name: 
shenx

This tutorial will provide an introduction to the Linux operating system, with particular attention paid to working from the command line. The tutorial will cover basics such as fundamental commands, editing files, understanding directories and permissions, and remote access.

Haploview

Software Support Level: 
Secondary Support
Software Description: 

Haploview is a graphical program for haplotype analysis. It can analyze thousands of SNPs (tens of thousands in command line mode) in thousands of individuals. It supports the following functionalities: LD haplotype block analysis- haplotype population frequency estimation- single SNP and haplotype association tests- permutation testing for association significance- implementation of Paul de Bakker's Tagger tag SNP selection algorithm- automatic download of phased genotype data from HapMap visualization and plotting of PLINK whole genome association results including advanced filtering options.

Software Access Level: 
Open Access
Software Categories: 
Software Interactive/GUI: 
No
General Linux Documentation: 

Haploview requires a large amount of memory so it is recommended that you request more memory through the isub command line:

isub -m 6gb
module load haploview
haploview

To run haploview with more memory (in megabytes) use the -memory option:

haploview -memory 2000

Haploview may report out-of-memory errors when working with large datasets on cl or blr nodes. Try logging out and reconnecting using isub until you are connected to a lab node, where Haploview runs without a problem.

For additional information

 

R

Software Description: 

R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.

Software Support Level: 
Primary Support
Software Access Level: 
Open Access
Citrix Documentation: 

To run this software under Windows, connect using instruction provided in our Windows systems page.  Once logged in, navigate to

Start > All Programs > R > R x64 $VERSION

$VERSION is the version number of the R installation. If you need to run long or memory-intensive jobs, use R on Linux instead. If you need more details, visit the official documentation.

We recommend that you install R packages in your home directory. It can be accomplished by typing the following in the R command prompt. You need to replace packagename with the actual package.

r <- getOption("repos");
r["CRAN"] <- "http://cran.rstudio.com/";
options(repos=r);
install.packages("packagename");

Some packages need external libraries such as gccgslfftw etc. You can find the requirements in the package documentation. These packages have to be loaded by using 'module load' command before using R. If you still experience issues, please contact help@msi.umn.edu.                          

PBS Example: 

Programs can be submitted to a queue using PBS script such as the one below.  You need to modify the parameters depending on the machine where the job is executed. By default, an R script runs only on one core.  If you need to use multiple cores and/or multiple nodes, use packages that are listed in the CRAN page on high performance computing. The most popular R parallel packages are snow, snowfall, Rmpi and parallel. 

#PBS -l nodes=1:ppn=8,mem=12gb,walltime=04:00:00
#PBS -m abe
cd /location/of/the/script
module load R
R CMD BATCH myscript.R
wait
Software Interactive/GUI: 
No
General Linux Documentation: 

To run this software interactively in a Linux environment run the commands:

module load R
R

Several versions of R are available, but the versions may be different on different platforms.To list all versions of R available on the machine, type

module avail R

We recommend that you install R packages in your home directory. It can be accomplished by typing the following in the R command prompt. You need to replace packagename with the actual package.

r <- getOption("repos");
r["CRAN"] <- "http://cran.rstudio.com/";
options(repos=r);
install.packages("packagename");

Some packages need external libraries such as gccgslfftw etc. You can find the requirements in the package documentation. These packages have to be loaded by using 'module load' command before using R. If you still experience issues, please contact help@msi.umn.edu.                          

 
 

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