ISCE2 installation guide

This guide provides instructions to install ISCE2 with Anaconda/Miniconda on a Linux/MacOS machine. NOTE: this is not the official installation guide. It only serves to help users to install ISCE2 on some common and most recent platforms. Please check the ISCE2 page for official guides and tutorials.

Linux with Anaconda3 : cmake with GPU support

Prepare a conda or conda virtual environment

  conda create -n isce2
  conda activate isce2

(Any python version 3.7 - 3.11 should work).

The following steps will install isce2 to $CONDA_PREFIX.

     echo $CONDA_PREFIX

Install required packages

  conda install -c conda-forge git cmake cython gdal h5py libgdal pytest numpy fftw scipy pybind11 shapely
  pip install opencv-python

opencv has complex dependencies, which causes long delay to the conda compatibility check. We recommend installing it with pip.

To compile/install mdx, you will also need

     conda install -c conda-forge openmotif openmotif-dev xorg-libx11 xorg-libxt xorg-libxmu xorg-libxft libiconv xorg-libxrender xorg-libxau xorg-libxdmcp poppler

NOTE: it seems that openmotif package is not actively maintained in conda. If you experience long delays in this step, please STOP and just use linux system installed openmotif. You may use the command ldconfig -p | grep libXm to check whether it exists. If not, install openmotif by

    # Ubuntu/Debian 
    sudo apt install libxm4
    # Redhat CentOS
    yum install motif, motif-devel

Compilers. GNU compilers coming with the system are recommended; GCC 4.8 - 13 are supported. ONly if you don't have access to a system installed compiler,) you may use conda gnu compilers,

    conda install gcc_linux-64 gxx_linux-64 gfortran_linux-64

To use GPU-accelerated modules, you will need a CUDA compiler, which is usually located at /usr/local/cuda or can be loaded by module load cuda. Note that CUDA compiler (nvcc) may have restrictions on host compilers, see CUDA Documentaion for more details. Note also that CUDA 12 has dropped support for devices < sm_50, such as K40. Please use CUDA 11 for these old devices.

Download the source package

 mkdir -p $HOME/tools/src
 cd $HOME/tools/src
 git clone https://github.com/isce-framework/isce2.git

Compile and install isce2

cd $HOME/tools/src/isce2
# create a build directory
mkdir build  && cd build
# use a symbolic link instead of specify -DPYTHON_MODULE_DIR=lib/python3.xx/site-packages
ln -sf `python3 -c 'import site; print(site.getsitepackages()[0])'` $CONDA_PREFIX/packages  
# run cmake config
cmake .. -DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX \
  -DCMAKE_CUDA_ARCHITECTURES=native \
  -DCMAKE_PREFIX_PATH=${CONDA_PREFIX} \
  -DCMAKE_BUILD_TYPE=Release 
# compile and install 
make -j && make install

Some common issues
- -DCMAKE_CUDA_ARCHITECTURES=native the native, or auto-detect gpu architecture option requres cmake >= 3.24. If you see a message like nvcc fatal : Unsupported gpu architecture 'compute_', you are using an old version of cmake and need to change native to your targeted gpu architecture(s). See details below.
- Also make sure that cmake has identified the correct python interpreter from conda. Sometimes, it uses the system installed python instead. In this case, you may guide find_python by adding -DPython_EXECUTABLE=`which python3`.
DCMAKE_INSTALL_PREFIX is where the package is to be installed. Here, we choose to install to the conda venv directly ($CONDA_PREFIX) such that the paths to isce2 commands/scripts are automatically set up, like other conda packages.
DPYTHON_MODULE_DIR (no longer needed with the symbolic link) is the directory to install Python scripts, defined relative to the DCMAKE_INSTALL_PREFIX directory. Please check your conda venv python3 version, and set it accordingly, e.g., python3.7 instead of python3.9. One method to check the site-packages directory for your Python version is to run the command
```
  python3 -c 'import site; print(site.getsitepackages())'
```
DCMAKE_CUDA_ARCHITECTURES targets optimizing the GPU code for a specific GPU architecture, or in terms of the CUDA Compute Capability, e.g., 60 for P100, 70 for V100, 80 for A100, 90 for H100, ... If the GPU is installed on the same machine you are compiling the code, you may simply use DCMAKE_CUDA_ARCHITECTURES=native to auto-config. If you plan to run the code on multiple architectures, use a list such as DCMAKE_CUDA_ARCHITECTURES="60;70;86", see CMake Manual for more details.
DCMAKE_PREFIX_PATH is for search path(s) of dependencies, such as gdal, fftw. Since we installed all dependencies through conda, we use ${CONDA_PREFIX}.
DCMAKE_BUILD_TYPE=(None, Debug, Release). Some isce2 modules (e.g. PyCuAmpcor) have debugging features which are turned on/off by the -DNDEBUG compilation flag. This flag is not included in Debug build type or not specified, i.e., debugging features are on. It is included in Release build type, and therefore debugging features are turned off. For end users, please use Release build type.

If cmake cannot locate the desired compilers correctly, you can enforce the choice of compilers by adding

-DCMAKE_C_COMPILER=/path/to/gcc -DCMAKE_CXX_COMPILER=/path/to/g++ -DCMAKE_Fortran_COMPILER=/path/to/gfortran

If something is wrong in the compilation and you would like to check the details
```
make VERBOSE=1
```

Check and Test

You may check whether ISCE2 is properly installed by

  cd $CONDA_PREFIX/bin
  ls -ltr 
  # you should see mdx, and other python apps are installed 
  cd ../lib/python3.x/site-packages
  ls -ltr
  # you should see isce2 and an additional link isce

You may try to run

  python3 -c 'import isce'
  topsApp.py -h 
  ...

Next time, all you need to do to load isce2 is to

  codna activate # if you install to the base 
  conda activate isce2 # if you install to an isce2 venv.

By default, the CUDA modules run on GPU device 0 (currently only one GPU per task is supported). If there are multiple tasks or multiple users sharing the same device, the program will run slow or even crash. If you have multiple GPUs installed (run nvidia-smi to check), you may spread your tasks to different GPUs, by using CUDA_VISIBLE_DEVICES=n to select the device, where n=0,1,... up to the number of GPUs installed. For example, to use device 2 (third GPU),

  export CUDA_VISIABLE_DEVICES=2
  topsApp.py ...
  # or one line
  CUDA_VISIBLE_DEVICES=2 topsApp.py ...

Linux with Anaconda3 : scons

Note: SCons with Conda doesn't work on Mac. You may need to use macports.

Note: If you plan to use Linux provided packages instead of Conda, please follow Ubuntu 18.04 example to create a SConfigISCE config file.

Install Anaconda or Minoconda. If you only run isce2 with venv, miniconda is recommended.

If you prefer, prepare a conda virtual environment

conda create -n isce2 python=3.8
conda activate isce2

Install required packages

conda install -c conda-forge git scons cython gdal h5py libgdal pytest numpy fftw scipy opencv pybind11 shapely

To compile/install mdx, you will also need

   conda install -c conda-forge openmotif openmotif-dev xorg-libx11 xorg-libxt xorg-libxmu xorg-libxft libiconv xorg-libxrender xorg-libxau xorg-libxdmcp

You will need to make a symbolic link for cython3,

   cd $CONDA_PREFIX/bin
   ln -sf cython cython3

If you plan to use conda installed GNU compilers (note that currently there are some compatibility issues of conda compiler with Redhat 7 systems, don't install gcc_linux-64, .... If you already made the following links, please delete them.)

   ln -sf x86_64-conda_cos6-linux-gnu-gcc gcc
   ln -sf x86_64-conda_cos6-linux-gnu-g++ g++
   ln -sf x86_64-conda_cos6-linux-gnu-gfortran gfortran
   ln -sf x86_64-conda_cos6-linux-gnu-ld ld
  
   # for some conda-forge builds (seems no longer an issue with python3.8)
   cd $CONDA_PREFIX/lib
   ln -sf libzstd.so.1.3.7 libzstd.so.1

Download isce2 for GitHub or prepare your own version

# create a directory to save source files
mkdir -p ${HOME}/tools/src 
cd {$HOME}/tools/src
# glone a copy from github
git clone https://github.com/isce-framework/isce2

The command shall pull a GitHub version of isce2 to your ${HOME}/tools/src/isce2 directory.

Configure a SConfigISCE file under, e.g. ${HOME}/.isce directory

PRJ_SCONS_BUILD=$HOME/build/isce_build
PRJ_SCONS_INSTALL=$ISCE_HOME
LIBPATH=$CONDA_PREFIX/lib
CPPPATH=$CONDA_PREFIX/include $CONDA_PREFIX/include/python3.8/ $CONDA_PREFIX/lib/python3.8/site-packages/numpy/core/include $CONDA_PREFIX/include/opencv4
FORTRAN=gfortran
CC=gcc
CXX=g++
FORTRANPATH=$CONDA_PREFIX/include
MOTIFLIBPATH=$CONDA_PREFIX/lib
X11LIBPATH=$CONDA_PREFIX/lib
MOTIFINCPATH=$CONDA_PREFIX/include
X11INCPATH=$CONDA_PREFIX/include
RPATH=$CONDA_PREFIX/lib
ENABLE_CUDA = True
CUDA_TOOLKIT_PATH=/usr/local/cuda  # use 'which nvcc' to verify

PRJ_SCONS_BUILD is a directory to save temporary compiled files
PRJ_SCONS_INSTALL is where the isce2 will be installed. We use a $ISCE_HOME to be defined later
LIBPATH is where to look for the shared libraries, such as gdal, fftw
CPPPATH is where to look for C/C++ head files (#include) for libraries
FORTRAN, CC, CXX are the Fortran/C/C++ compilers to be used
MOTIFLIBPATH ... X11INCPATH are to set lib and include paths for motif and x11 libraries.
- for Ubuntu 18.04, set MOTIFLIBPATH1 and X11LIBPATH to /usr/lib/x86_64-linux-gnu/ and set MOTIFINCPATH and X11INCPATH to /usr/include.
- for Redhat or CentOS 7, set MOTIFLIBPATH1 and X11LIBPATH to /lib64 and set MOTIFINCPATH and X11INCPATH to /usr/include.
- for conda installed packages, set them as $CONDA_PREFIX/lib and $CONDA_PREFIX/include.
ENABLE_CUDA = True/False whether to include some GPU/CUDA accelerated modules. If enabled, please also specify CUDA_TOOLKIT_PATH to where CUDA SDK is installed. Some manual configuration might be needed:
- CUDA SDK Versions 9 and above are recommended.
- The CUDA compiler 9 & 10 by default targets NVIDIA GPUs with compute capability 3.5 (K40, K80). CUDA 11 uses sm_52 as default. If you prefer to compile CUDA code best suited to the GPU you have, find env['ENABLESHAREDNVCCFLAG'] in ${HOME}/tools/src/isce2/scons_tools/cuda.py file, find the line env['ENABLESHAREDNVCCFLAG'] = '-std=c++11 -shared, add -arch=sm_35 for K40/K80, -arch=sm_60 for P100, -arch=sm_61 for GTX1080, -arch=sm_70 for V100.

Some settings for environment variables before compile/install. You need to specify three environment variables

CONDA_PREFIX where Anaconda3 is installed
ISCE_HOME where isce2 will be installed
SCONS_CONFIG_DIR where the SConfigISCE is located. if they are not set. Check by, e.g., echo $CONDA_PREFIX.

For csh,

   setenv ISCE_HOME ${HOME}/tools/isce
   setenv SCONS_CONFIG_DIR ${HOME}/.isce

and for bash,

   export ISCE_HOME=${HOME}/tools/isce
   export SCONS_CONFIG_DIR=${HOME}/.isce

Compile/install isce2

cd ${HOME}/tools/src/isce2
scons install

If successful, you should obtain a compiled isce2 at $ISCE_HOME or $HOME/tools/isce.

Some common problems or questions:

if you use conda installed X11 motif libraries, you might see an error libXm.so not found reported by scons. You may neglect and proceed; these libraries will be linked properly. But if you see error messages about gdal or fftw, please stop and check.

Set up environment variables to load/usr isce2.

use environment module, .e.g., module load/unload isce2.mod where an example of isce2.mod is provided below.

#%Module
module-whatis {Description: ISCE2-github}
set root $HOME/tools/isce
prepend-path	LD_LIBRARY_PATH	$root/lib
prepend-path	LIBRARY_PATH	$root/lib
prepend-path	PATH		$root/bin:$root/applications
prepend-path	PYTHONPATH	$HOME/tools:$root:$root/applications:$root/components:$root/library
setenv 		ISCE_HOME       $root

Note that in order to import isce from python, you need to use the isce as the installation directory name and also set the directory where isce is located (in above case, $HOME/tools) to PYTHONPATH.

use a resource file to load as source isce2.rc. For csh,

# isce2.cshrc
setenv ISCE_HOME $HOME/tools/isce
setenv PATH $ISCE_HOME/bin\:$ISCE_HOME/applications\:$PATH
setenv LD_LIBRARY_PATH $ISCE_HOME/lib\:$LD_LIBRARY_PATH
# check whether PYTHONPATH exists 
if ( ! $?PYTHONPATH ) then
  setenv PYTHONPATH $HOME\:$ISCE_HOME\:$ISCE_HOME/applications\:$ISCE_HOME/components\:$ISCE_HOME/library
else
  setenv PYTHONPATH $HOME\:$ISCE_HOME\:$ISCE_HOME/applications\:$ISCE_HOME/components\:$ISCE_HOME/library\:$PYTHONPATH
endif

For bash,

  # isce2.rc
  export ISCE_HOME=$HOME/tools/isce
  export PATH=$ISCE_HOME/bin:$ISCE_HOME/applications:$PATH
  export LD_LIBRARY_PATH=$ISCE_HOME/lib:$LD_LIBRARY_PATH
  export PYTHONPATH=$ISCE_HOME:$ISCE_HOME/applications:$ISCE_HOME/components:$ISCE_HOME/library:$HOME/tools:$PYTHONPATH

Common questions/problems

MacOSX with Anaconda3 and homebrew: Apple Silicon

(Testd on macOS Sonoma 14.1.2. This is the recommended method for MacOS - all packages are pre-compiled. However, after a major MacOS upgrade, e.g., from 13 to 14, a re-installation of Xcode Command Line Tools, conda, homebrew is recommended.)

Install Xcode (or command line tools), Conda and gcc/g++/gfortran Compiler

Install an osx-arm64 build of Anaconda3 or Miniconda3 (recommended).

Taking miniconda as an example, you may follow the Quick Command Line Install method

  mkdir -p ~/miniconda3
  curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh -o ~/miniconda3/miniconda.sh
  bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
  rm -rf ~/miniconda3/miniconda.sh

Install Homebrew (the pkg installer is the easiest method, download from Homebrew Releases). For Apple Silions (osx-arm64), brew is installed to /opt/homebrew.

    export PATH="/opt/homebrew/bin:$PATH"

and then install gfortran (current version GCC 13.2)

    brew install gfortran

If you need mdx (slc viewing software), install openmotif here (osx-arm64 version currently not available from conda)

    brew install openmotif

Also install XQuartz.

Prepare a conda or conda virtual environment

conda create -n isce2
conda activate isce2

The following steps will install isce2 to $CONDA_PREFIX.

   echo $CONDA_PREFIX

Make a link to make the installation path easier (-DPYTHON_MODULE_DIR not longer need)

   ln -sf `python3 -c 'import site; print(site.getsitepackages()[0])'` $CONDA_PREFIX/packages

Install required packages

conda install git cmake cython gdal h5py libgdal pytest numpy fftw scipy pybind11 shapely
pip install opencv-python

opencv has complex dependencies, which causes long delay to the conda compatibility check. We recommend installing it with pip.

Compile and install isce2

Download ISCE2 from github

    git clone https://github.com/isce-framework/isce2.git

Compile ISCE2 with cmake,

    cd isce2
    mkdir build && cd build
    cmake .. -DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX \
      -DCMAKE_PREFIX_PATH=${CONDA_PREFIX} \
      -DCMAKE_C_COMPILER="/opt/homebrew/bin/gcc-13" \
      -DCMAKE_CXX_COMPILER="/opt/homebrew/bin/g++-13" 
    make -j # to use multiple threads
    make install

We use gcc from homebrew instead of Apple Clang because of some compatibility issue (some source codes need to be updated).

Config and run isce2

If you follow the above steps, ISCE2 packages are installed to $CONDA_PREFIX/packages/isce2. You will only need to add the path to stack apps,

    export ISCE_HOME="$CONDA_PREFIX/packages/isce"
    export PATH="$ISCE_HOME/applications:$PATH"

If you have installed ISCE2 to a custom directory, e.g., $HOME/apps/isce2, with -DCMAKE_INSTALL_PREFIX=$HOME/apps/isce2 cmake option, you need to

    export ISCE_INSTALL_ROOT="$HOME/apps/isce2"
    export ISCE_HOME="$ISCE_INSTALL_ROOT/packages/isce"
    export PATH="$ISCE_HOME/applications:$ISCE_INSTALL_ROOT/bin:$PATH"
    export PYTHONPATH="$ISCE_INSTALL_ROOT/packages:$PYTHONPATH"

You may try the following to check whether ISCE2 has been properly installed,

    python3 -c "import isce"

To use mdx, you will need XQuartz.

    mdx.py xxxxx.slc 
    # show the slc picture (.xml description file needed)

Enjoy!

MacOSX with Anaconda3 : Intel

This is an old guide for Intel Macs (osx-64). It may also work for Apple Silicons with Rosetta 2, but may experience complexities on clang/gcc compilers for new versions of macOS.

Please follow the instructions for Linux. You may need to install xcode or command-line-tools. GPU modules are not supported for MacOSX, unless you use an external GPU with NVIDIA cards. You will then need to install NVIDIA driver and CUDA.

For Apple Silicon (M1, M2, ...), you may use the regular (x86_64) Conda releases (continue to work with Rosetta 2). Or you may install the native arm64 version from Anaconda, or Miniforge. However, openmotif is not currently supported by native arm64. If you need mdx, please use the x86_64 release with Rosetta 2.

Example with MacOSX 11.5.2 (Big Sur) and Apple Clang 12.0.5.

Prepare a conda or conda virtual environment

conda create -n isce2
conda activate isce2

The following steps will install isce2 to $CONDA_PREFIX.

   echo $CONDA_PREFIX

Install required packages

conda install git cmake cython gdal h5py libgdal pytest numpy fftw scipy pybind11
pip install opencv

opencv has complex dependencies, which causes long delay to the conda compatibility check. We recommend installing it with pip.

To compile/install mdx, you will also need

   conda install openmotif openmotif-dev xorg-libx11 xorg-libxt xorg-libxmu xorg-libxft libiconv xorg-libxrender xorg-libxau xorg-libxdmcp

Compilers

If you already have Xcode installed,

   sudo xcode-select --switch /Applications/Xcode.app/Contents/Developer
   which clang # show /usr/bin/clang
   clang --version # Apple clang version  12.0.5 (clang-1205.0.22.11)

If not, you may install the full version of Xcode, or simply the Command Line Tools,

  sudo xcode-select --install
  sudo xcode-select --switch /Library/Developer/CommandLineTools

Install gfortran through brew

   brew install gfortran
   which gfortran # show /usr/local/bin/gfortran
   gfortran --version # GNU Fortran (Homebrew GCC 11.2.0) 11.2.0

Or you may simply download the binary from HPC MacOSX: they have pre-compiled versions gfortran-x.x-bin.tar.gz for all MacOSX systems, including Apple Silicon.

Compile and install isce2

cd $HOME/tools/src/isce2
mkdir build  && cd build
cmake .. -DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX -DPYTHON_MODULE_DIR=lib/python3.9/site-packages  -DCMAKE_PREFIX_PATH=${CONDA_PREFIX}
make -j # to use multiple threads
make install

Change cmake options if necessary, e.g., PYTHON_MODULE_DIR to your installed python version. Enjoy!

Note that after each major MacOSX update, please try to update (or reinstall) Command Line Tools and update Conda.

You may notice warnings such as was built for newer macOS version (11.5) than being linked (11.0). It is in general safe to neglect these warnings. To suppress the warnings, you may add -DCMAKE_OSX_DEPLOYMENT_TARGET=11.5 to cmake command line.

MacOSX with Macports : Apple Silicon with mdx

(Tested on macOS Ventura 13.5.1)

Install Xcode (or Command Line Tools) and Macports

Follow the Macports Guide to download and install Macports. All the files, by default, will be installed to /opt/local. The PATH will also be automatically added to your .zprofile or .profile. If not, please run

    export PATH="/opt/local/bin:/opt/local/sbin:$PATH"

It is a good idea to perform a update at first,

    sudo port -v selfupdate

To run mdx (the SLC viewing software), please also install XQuartz.

Install required packages

Compiler GCC/G++/Gfortran and OpenMP

    sudo port install gcc12 libomp
    sudo port select --set gcc mp-gcc12

Python and other libraries, (note: some additional python packages might be needed at runtime, you may always use sudo port install py311-xxxx to install them later.)

    sudo port install cmake python311 py311-cython py311-numpy py311-scipy py311-pybind11 pybind11 hdf5 py311-gdal fftw-3 fftw-3-single py311-opencv4-devel
    sudo port select --set python python311
    sudo port select --set python3 python311
    sudo port select --set cython cython311
    sudo port select --set gdal py311-gdal
    sudo ln -sf `python3 -c 'import site; print(site.getsitepackages()[0])'` /opt/local/packages

(Optional) To use mdx, install Openmotif

    sudo port install openmotif

Install ISCE2

Download ISCE2 from GitHub

    git clone https://github.com/isce-framework/isce2.git

Compile ISCE2 with cmake,

    cd isce2
    mkdir build && cd build
    cmake .. -DCMAKE_INSTALL_PREFIX=/opt/local \
      -DCMAKE_C_COMPILER=/opt/local/bin/gcc \
      -DCMAKE_CXX_COMPILER=/opt/local/bin/g++ \
      -DCMAKE_PREFIX_PATH="/opt/local" \
      -DOpenMP_C_FLAGS="-fopenmp=lomp" \
      -DOpenMP_CXX_FLAGS="-fopenmp=lomp" \
      -DOpenMP_C_LIB_NAMES="libomp" \
      -DOpenMP_CXX_LIB_NAMES="libomp" \
      -DOpenMP_libomp_LIBRARY="/opt/local/lib/libomp/libomp.dylib" \
      -DOpenMP_CXX_LIB_NAMES="libomp" \
      -DPython_ROOT_DIR="/opt/local/Library/Frameworks/Python.framework/Versions/3.11/"  
    make -j 
    sudo make install

(you may safely neglect the OpenCV warning.) Here, the installation path is set to /opt/local, or MacPorts. You may choose a different directory, e.g., $HOME/apps/isce2. But you will need to set PATH and PYTHONPATH manually by yourself.

Config and run isce2

mdx command is installed to /opt/local/bin while the rest is installed to /opt/local/packages/isce2 (or the actual location /opt/local/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/isce2. You may try the following to check whether ISCE2 has been properly installed,

    python3 -c "import isce"
    # return "Using default ISCE Path: /opt/local/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/isce".

To use some python apps, it is convenient to set up some environmental variables,

    #isce2.rc
    export ISCE_HOME="/opt/local/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/isce"
    export PATH="$ISCE_HOME/applications:$PATH"

To use mdx, you will need XQuartz.

    mdx.py xxxxx.slc 
    # show the slc picture (.xml description file needed)

(If you have a "cannot open DISPLAY" error, check here. )

Problems & Questions, please post on the Issue.

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ISCE2 installation guide

Contents

Linux with Anaconda3 : cmake with GPU support

Linux with Anaconda3 : scons

MacOSX with Anaconda3 and homebrew: Apple Silicon

MacOSX with Anaconda3 : Intel

MacOSX with Macports : Apple Silicon with mdx

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ISCE2 installation guide

Contents

Linux with Anaconda3 : cmake with GPU support

Linux with Anaconda3 : scons

MacOSX with Anaconda3 and homebrew: Apple Silicon

MacOSX with Anaconda3 : Intel

MacOSX with Macports : Apple Silicon with mdx

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