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Infrastructure > CerebroRocks > CR_AppsInstalled

Cerebro Rocks: Cluster's Applications

We have a variety of applications to be used by the LONI users who access the Cranium cluster. We use cerebro-rcc.loni.ucla.edu to build/install/upgrade a needed application. Once the application is ready to be used on production, we proceed to copy it into cerebro-rocks.loni.ucla.edu and then, propagate it into all the compute nodes on the cluster. We use rsync as method of propagation having cerebro-rocks as the rsync server. The applications installed on the Cranium (Cerebro Rocks) cluster are shown as follow:



Analyis of Functional Neuro Images

AFNI is a set of C programs for processing, analyzing, and displaying functional MRI (FMRI) data - a technique for mapping human brain activity. It runs on Unix+X11+Motif systems, including SGI, Solaris, Linux, and Mac OS X. It is available free (in C source code format, and some precompiled binaries) for research purposes.

Building the application

1. Go to build dir
        # cd /tmp/hugo

2. Download binaries from http://afni.nimh.nih.gov/afni/download/afni/releases/latest
        o Download AFNI/SUMA Software latest for Linux (Linux gcc33_64)
        o filename: linux_gcc33_64.tar.gz

3. Uncompress the tar file,         # tar -zxvf linux_gcc33_64.tar.gz
        # cd linux_gcc33_64
        # cp -f * /usr/local/afni-2007529-1644_64bit/bin/.
        # mv /usr/local/afni-2007529-1644_64bit/bin/README* /usr/local/afni-2007529-1644_64bit/.

4. Add AFNI Matlab library
        o Download AFNI Matlab Library latest for all platforms
        o filename: afni_matlab.tgz
        o http://afni.nimh.nih.gov/afni/download/afnimatlab/releases/latest

5. Uncompress the tar file,
        # tar -zxvf afni_matlab.tgz
        # cd afni_matlab
        # mv matlab /usr/local/afni-2007529-1644_64bit/.

6. Add AFNI Sample Data
        o Download AFNI/SUMA Sample Data latest for all platforms
        o filenames: AFNI_data1.tgz, AFNI_data2.tgz
        o http://afni.nimh.nih.gov/afni/download/data/releases/latest

7. Uncompress the tar file,
        # tar -zxvf AFNI_data1.tgz
        # cp -rf AFNI_data1 /usr/local/afni-2007529-1644_64bit/dataSample/.
        # tar -zxvf AFNI_data2.tgz
        # cp -rf AFNI_data2 /usr/local/afni-2007529-1644_64bit/dataSample/.

8. Add SUMA Sample Data
        o Download AFNI/SUMA Sample Data latest for all platforms
        o filenames: SUMA_demo.tgz, SUMA_StandardMeshes.tgz

9. Uncompress the tar file,
        # tar -zxvf SUMA_demo.tgz
        # cp -rf suma_demo /usr/local/afni-2007529-1644_64bit/sumaSample/.
        # tar -zxvf SUMA_StandardMeshes.tgz
        # cp -rf std_mashes /usr/local/afni-2007529-1644_64bit/sumaSample/.

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Automated Image Registration

AIR allows automated registration of 3D (and 2D) images within and across subjects and within and sometimes across imaging modalities. AIR source code written in C is available to the research community free of charge. The code can be compiled for UNIX, PC or Macintosh platforms. Only source code is available (no executables).

Building the application

1) Adquired code from /cxfs/tmp/sysadm/air5.2.5
        - Copied to /tmp/air5.2.5

2) ./configure --prefix=/tmp/air5.2.5/bin
        o To compile the extended binaries, edit
                - /tmp/hugo/air5.2.5/Makefile
                - /tmp/hugo/air5.2.5/src/Makefile

         as in Makefile.txt and Makefile-src.txt respectively.
         Be careful with the TAB spaces on the Makefiles.

3) make all

4) make install

5) Copy binaries
        # cp /tmp/air5.2.5/bin/* /usr/local/air5.2.5_64_16/bin/.

6) For 8 and 16 bits binaries, edit src/config.h
        #define AIR_CONFIG_OUTBITS 16
   to
        #define AIR_CONFIG_OUTBITS 8

7) For binaries compiled at 32 bits, set the CFLAGS and CXXFLGS to "-02 -m32" before step (2)

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Brainsuite

BrainSuite is a magnetic resonance (MR) image analysis tool designed for identifying tissue types and surfaces in MR images of the human head.

Building the application

1. Copied exec files from David Shattuck's directory:
        # cd /usr/local/brainsuite_32bit/bin
        # cp /nethome/users/shattuck/experimental/i386-redhat-linux-gnu/bfc07a_i386-redhat-linux-gnu .
        # cp /nethome/users/shattuck/experimental/i386-redhat-linux-gnu/bse07a_i386-redhat-linux-gnu .
        # cp /nethome/users/shattuck/experimental/i386-redhat-linux-gnu/pvc07a_i386-redhat-linux-gnu .

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Fast Lexical Analyzer Generator

Flex is a tool for generating programs that recognize lexical patterns in text. There are many applications for Flex, including writing compilers in conjunction with GNU Bison. Flex is a free implementation of the well known Lex program. It features a Lex compatibility mode, and also provides several new features such as exclusive start conditions.

Building the application

# used GNU Make 3.80

1. Uncompress the tar file,
        # cd /data/hugo
        # tar -zxvf flex-2.5.31.tar.gz

2. Build the package,
        # ./configure --prefix=/usr/local/flex-2.5.31_64bit
        # make
        # make install

3. Copy executable into /usr/local/bin
        # cp -rf /usr/local/flex-2.5.31_64bit/bin/flex /usr/local/bin/.

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Fast Light Toolkit

FLTK (pronounced "fulltick") is a cross-platform C++ GUI toolkit for UNIX®/Linux® (X11), Microsoft® Windows®, and MacOS?® X. FLTK provides modern GUI functionality without the bloat and supports 3D graphics via OpenGL?® and its built-in GLUT emulation.

Building the application

1. uncompress tar file,
        # cd /data/hugo
        # tar -zxvf fltk-1.1.7.tar.gz
        # cd fltk-1.1.7

2. configure the package
        # mkdir /usr/local/fltk-1.1.7
        # ./configure --prefix=/usr/local/fltk-1.1.7 --libdir=/usr/local/lib

3. build the package,
        # make ; make install

4. copy libraries to the $prefix
        # cp /usr/local/lib/libfltk* /usr/local/fltk-1.1.7_64bit/lib

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Free OpenGL Utility Toolkit

freeglut is a completely OpenSourced alternative to the OpenGL Utility Toolkit (GLUT) library. GLUT was originally written by Mark Kilgard to support the sample programs in the second edition OpenGL 'RedBook'. Since then, GLUT has been used in a wide variety of practical applications because it is simple, widely available and highly portable. GLUT (and hence freeglut) allows the user to create and manage windows containing OpenGL contexts on a wide range of platforms and also read the mouse, keyboard and joystick functions.

Building the application

1. Download the code from http://freeglut.sourceforge.net/index.php#download,

2. uncompress the source code,
        # cd /tmp/hugo
        # tar -jxvf freeglut-2.4.0.tar.bz2

3. configure the package,
        # ./configure --prefix=/usr/local/freeglut-2.4.0_64bit

4. build the package,
        # make
        # make install

5. copy libraries into /usr/local/lib
        # cp -f /usr/local/freeglut-2.4.0_64bit/lib/* /usr/local/lib/.

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FreeSurfer

FreeSurfer is a set of automated tools for reconstruction of the brain’s cortical surface from structural MRI data, and overlay of functional MRI data onto the reconstructed surface.

Building the application

1. Uncompress the application,
        # cd /tmp/hugo
        # tar -C /usr/local -zxvf freesurfer-3.0.5.tar.gz

2. A license file is required to enable the tools. One can be obtained for free by registering at: https://surfer.nmr.mgh.harvard.edu/registration.html

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FMRIB Software Library

FSL is a comprehensive library of analysis tools for FMRI, MRI and DTI brain imaging data, written mainly by members of the Analysis Group, FMRIB, Oxford, UK. FSL runs on Apple, PCs (Linux and Windows) and Sun, and is very easy to install.

Building the application

1. download code from http://www.fmrib.ox.ac.uk/fsl,

2. uncompress the tar file
        # tar -C /usr/local -zxvf /cxfs/tmp/sysadm/fsl-4.0.1-sources.tar.gz

3. to build the application
        # mv /usr/local/fsl /usr/local/fsl-4.0.1_64bit
        # cd /usr/local/fsl-4.0.1_64bit

4. set the main FSL environment variable
        # export FSLDIR=/usr/local/fsl-4.0.1_64bit

5. source the FSL environment setup script
        # . ${FSLDIR}/etc/fslconf/fsl.sh

6. check if your machine/compiler is supported by default
        # ls $FSLDIR/config/$FSLMACHTYPE

        ---> if not, select the closest match from the directories in $FSLDIR/config and do the following

        # cp -r $FSLDIR/config/linux_64-gcc4.1 $FSLDIR/config/$FSLMACHTYPE

7. build the application
        # ./build

8. if you want to re-make a particular package in $FSLDIR/src (e.g. flirt) then first set the FSLDEVDIR environment variable to the same as FSLDIR and then just type
        # make install

inside the relevant directory.

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GNU Compiler Collection

The GNU Compiler Collection includes front ends for C, C++, Objective-C, Fortran, Java, and Ada, as well as libraries for these languages (libstdc++, libgcj,...).

Building the application

1. download code from http://gcc.gnu.org/mirrors.html,

2. uncompress the tar file
        # tar -C /tmp/hugo -jxvf /cxfs/tmp/sysadm/gcc-4.2.0.tar.bz2

3. build the application
        # cd /tmp/hugo/gcc-4.2.0
        # ./configure --prefix=/usr/local/gcc-4.2.0_64bit

        ---> be sure you have installed glibc-devel for both 32 and 64bits
                currently: glibc-devel-2.3.4-2.36

        # make

        ---> create backups for the executables of the current gcc version in /usr/bin

        # make install

4. create symlinks or copy new execs into /usr/bin

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Insight Applications

The following applications illustrate the use of ITK in real-world medical imaging applications. Note these application are found in the InsightApplications module. They differ from the Insight/Examples examples in that they use other systems such as VTK, FLTK and Qt to create turn-key applications. Please make sure that you can compile and link the examples found in Insight/Examples prior to building these applications. The applications are often difficult to compile and run.

Building the application

1. Uncompress the tar file,
        # cd /tmp/hugo
        # tar -zxvf _InsightApplications_-3.2.0.tar.gz

2. Create build directory,
        # mkdir /usr/local/_InsightApplications_-3.2.0_64bit

3. Configure the package,
        # ccmake .

        Use flags:
                BUILD_SHARED_LIBRARIES ON
                ITK_DIR /tmp/hugo/InsightToolKit-3.2.0 (source code)
                CMAKE_INSTALL_PREFIX /usr/local/InsightApplications-3.2.0_64bit

        Hit [c] to configure,
        Hit [g] to generate and exit,

4. Build the package,
        # make
        # make install

5. Copied libraries into /usr/local/lib
        # cp -vf /usr/local/InsightApplications/lib/* /usr/local/lib/.

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Insight Toolkit

ITK is an open-source software system to support the Visible Human Project. Currently under active development, ITK employs leading-edge segmentation and registration algorithms in two, three, and more dimensions.

Building the application

# used ccmake version 2.4-patch 6 (2.4-patch 5 used on cerebellum)
# used GNU Make 3.80

1. Uncompress the tar file,
        # cd /data/hugo
        # tar -zxvf _InsightToolkit_-3.2.0.tar.gz

2. Create build directory,
        # mkdir /usr/local/InsightToolkit-3.2.0

3. Configure the package,
        # ccmake /data/hugo/InsightToolkit-3.2.0

        Use flags:
                BUILD_SHARED_LIBRARIES ON
                BUILD_EXAMPLES 0N
                BUILD_TESTING ON
                CMAKE_INSTALL_PREFIX /usr/local/InsightToolkit-3.2.0

        Hit [c] to configure,
        Hit [g] to generate and exit,

4. Build the package,
        # make
        # make install

5. Copied execs from build dir to $prefix dir
        # cp /data/hugo/InsightToolkit-3.2.0/bin/* /usr/local/InsightToolkit-3.2.0/bin/.

6. Copied library dir into /usr/local/lib
        # cp -rvf /usr/local/InsightToolkit/lib/InsightToolkit /usr/local/lib/.

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Java SE Development Kit

The Java SE Development Kit (JDK) includes the Java Runtime Environment (JRE) and command-line development tools that are useful for developing applets and applications.

Building the application

1. download the application from http://java.sun.com/javase/downloads/index.jsp,

2. install the application,
        # cd /tmp/hugo
        # chmod +x jdk-6u2-linux-amd64-rpm.bin
        # ./jdk-6u2-linux-i586-rpm.bin

        ---> follow the instructions

3. copy /usr/java into /usr/local

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LONI Applications

  • URL: Unknown
  • Current Version: Unknown
  • Installed Version: Unknown
  • Installed at: Unknown

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LONI Data

  • URL: Unknown
  • Current Version: Unknown
  • Installed Version: Unknown
  • Installed at: Unknown

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LONI Jar Files

  • URL: Unknown
  • Current Version: Unknown
  • Installed Version: Unknown
  • Installed at: Unknown

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LONI Scripts

  • URL: Unknown
  • Current Version: Unknown
  • Installed Version: Unknown
  • Installed at: Unknown

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Matlab

MATLAB is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages such as C, C++, and Fortran.

Building the application

1. download code from http://www.mathworks.com,

2. uncompress the tar file
        # cd /hugo/tmp/build-matlab
        # tar -xvf boot.ftp

3. build the application
        # ./install

        ---> follow all the instructions from the GUI

4. use SPM5
        ---> copy all the content of the SPM5 directory into the Matlab directory
        # cp -rf /usr/local/spm5 /usr/local/matlab7.4_64bit/.

        ---> recompile the mex files with the current gcc compiler
        # cd /usr/local/matlab7.4_64bit/spm5/src
        # make & make install

5. Include SPM5 into the Matlab path
        setenv MATLABPATH /usr/local/matlab7.4_64bit/spm5

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Montreal Neurological Institute

The MNI is a teaching and research institute of McGill University in which multidisciplinary teams of basic and clinician scientists work to generate fundamental information about the nervous system and to apply that knowledge to understanding and treating neurological diseases.

Building the application

System:
        Linux x86_64

Compiler:
        3.4.5

Procedure:
1 netcdf-3.5.0
        o setenv CPPFLAGS "-Df2cFortran"
        o setenv FC /usr/bin/g77
        o setenv FFLAGS "-Wno-globals"
        o setenv CXX /usr/bin/g++
        o ./configure --prefix=/usr/local/mni
        o make ; make install

2. minc-1.4.0
        o ./configure --prefix=/usr/local/mni --with-build-path=/usr/local/mni
        o make ; make install

3. mni_autogen-0.98v
        o ./configure --prefix=/usr/local/mni --with-build-path=/usr/local/mni
        o make ; make install

4. ebtks-1.5.0
        o ./configure --prefix=/usr/local/mni --with-build-path=/usr/local/mni
        o make ; make install

5. N3-1.10
        o ./configure --prefix=/usr/local/mni --with-build-path=/usr/local/mni
        o make ; make install

6. bicpl-1.4.2
        o ./configure --prefix=/usr/local/mni --with-build-path=/usr/local/mni
        o make ; make install

7. conglomerate-1.5
        o ./configure --prefix=/usr/local/mni --with-build-path=/usr/local/mni
        o make ; make install

8. mni_perllib-0.07
        o setenv PERLLIB /usr/local/mni/lib
        o perl Makefile.PL PREFIX=/usr/local/mni INSTALLDIRS=perl
        o make ; make install

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netpbm

Netpbm is a toolkit for manipulation of graphic images, including conversion of images between a variety of different formats. There are over 300 separate tools in the package including converters for about 100 graphics formats. Examples of the sort of image manipulation we're talking about are: Shrinking an image by 10%; Cutting the top half off of an image; Making a mirror image; Creating a sequence of images that fade from one image to another.

Building the application

# used GNU Make 3.80

# requires:
        o flex/lex (generate programs for lexical tasks)
        o tiff libraries

1. Uncompress the tar file,
        # cd /data/hugo
        # tar -zxvf netpbm-10.26.42.tgz

2. Build the package. See doc/INSTALL.
        # ./configure
                o use static library
                o define tiff libraries and paths when required
        # make
        # make package pkgdir=/usr/local/netpbm-10.26.42_64bit

3. To gather all the installable parts into a specified directory, and finally
        # installnetpbm

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nifticlib

niftilib is a collection of i/o routines for the nifti1 neuroimage data format. C (nifticlib), Java (niftijlib), Matlab (niftimatlib), and Python (pynifti) code is available. Information about the nifti format is available at http://nifti.nimh.nih.gov/df

Building the application

# used GNU Make 3.80

1. Uncompress the tar file,
        # cd /data/hugo
        # tar -C /usr/local -zxvf nifticlib-0.3.tar.gz
        # cd /usr/local ; mv nifticlib-0.3 nifticlib-0.3_64bit

2. Build the package,
        # make all

3. Copy libraries into /usr/local/lib
        # cp -rf /usr/local/nifticlib-0.3_64bit/lib /usr/local/lib/.

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R Project for Statistical Computing

R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.

Building the application

# based on R. Magsipoc's compilation on cerebellum (3/6/07)
#
# Build latest version of readline, 64-bit, first with default flags

1. Set flags,
        o setenv CFLAGS "-O2 -m64"
        o setenv CXXFLAGS "-O2 -m64"
        o setenv CPPFLAGS "-I/usr/local/include -I/usr/include"
        o setenv LDFLAGS "-L/usr/local/lib -L/usr/lib64"

2. Uncompress package,
        # cd /tmp/hugo ; tar -zxvf R-2.4.1.tar.gz
        # cd /tmp/hugo/R-2.4.1

3. Configure and build package,
        # ./configure --prefix=/usr/local/R-2.4.1_64bit
        # make
        # make check
        # make install

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readline

The GNU Readline library provides a set of functions for use by applications that allow users to edit command lines as they are typed in. Both Emacs and vi editing modes are available. The Readline library includes additional functions to maintain a list of previously-entered command lines, to recall and perhaps reedit those lines, and perform csh-like history expansion on previous commands.

Building the application

1. Set flags,
        o setenv CFLAGS "-O2 -m64"
        o setenv CXXFLAGS "-O2 -m64"
        o setenv CPPFLAGS "-I/usr/local/include -I/usr/include"
        o setenv LDFLAGS "-L/usr/local/lib -L/usr/lib64"

2. Uncompress package,
        # cd /tmp/hugo ; tar -zxvf readline-5.2.tar.gz
        # cd /tmp/hugo/readline-5.2

3. Configure and build package,
        # ./configure --prefix=/usr/local/readline-5.2_64bit
        # make
        # make install

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Shape Tools

Building the application

Copied directory from Craig Schwartz.

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Statistical Parametric Mapping

Statistical Parametric Mapping refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional imaging data. These ideas have been instantiated in software that is called SPM. The SPM is a MATLAB software package and has been designed for the analysis of brain imaging data sequences. The sequences can be a series of images from different cohorts, or time-series from the same subject. The current release is designed for the analysis of fMRI, PET, SPECT, EEG and MEG.

Building the application

1. download code from http://www.fil.ion.ucl.ac.uk/spm/software/download.html,

2. uncompress the tar file
        # tar -C /usr/local -zxvf /cxfs/tmp/sysadm/MatLab/spm5.tar.gz

3. recompile the mex files to work with the current GCC version
        # cd /usr/local/spm5/src
        # make && make install

4. To enable this package for Matlab, copy the complete directory into the Matlab directory and include it into the Matlab Path
        # cp -rf /usr/local/spm5 /usr/local/matlab/.

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Tagged Image File Format

This software provides support for the Tag Image File Format (TIFF), a widely used format for storing image data. Included in this software distribution is a library, libtiff, for reading and writing TIFF, a small collection of tools for doing simple manipulations of TIFF images, and documentation on the library and tools. Libtiff is a portable software, it was built and tested on various systems: UNIX flavors (Linux, BSD, Solaris, MacOS X), Windows, OpenVMS. It should be possible to port libtiff and additional tools on other OSes.

Building the application

# used GNU Make 3.80

1. Uncompress the tar file,
        # cd /data/hugo
        # tar -zxvf tiff-3.8.2.tar.gz

2. Build the package,
        # ./configure --prefix=/usr/local/tiff-3.8.2_64bit
        # make
        # make install

3. Copy libraries into /usr/local/lib
        # cp -rf /usr/local/tiff-3.8.2_64bit/lib/* /usr/local/lib/.

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Visualization Toolkit

The Visualization Toolkit (VTK) is an open source, freely available software system for 3D computer graphics, image processing, and visualization used by thousands of researchers and developers around the world. VTK consists of a C++ class library, and several interpreted interface layers including Tcl/Tk, Java, and Python.

Building the application

1. uncompress the tar file,
        # cd /tmp/hugo
        # tar -zxvf vtk-5.0.2.tar.gz
        # cd VTK

2. configure package,
        # ccmake .

        Use the flags:
                BUILD_SHARED_LIBS ON
                CMAKE_INSTALL_PREFIX /usr/local/vtk-5.0.2
                VTK_DATA_ROOT /tmp/hugo/VTK
                VTK_USE_RENDERING ON
                VTK_USE_RPATH OFF
                VTK_WRAP_TCL ON

3. build package,
        # mkdir /usr/local/vtk-5.0.2
        # make ; make install

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Revised: r1.5 - 01 Jul 2008 - 21:50 - JonathanPierce
 
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