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arpack-ng - 3.9.0
[ Vikas Sharma ]
* Improve README.
[ Fabien Péan ]
* CI: Enable job `windows_latest_cmake` to run all tests
* CMake: Fix BLAS and LAPACK static library order needed to consume the library on Windows with static linkage
README.md
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ARPACK-NG is a collection of Fortran77 subroutines designed to solve large scale
eigenvalue problems.
# arpack-ng [![arpack-ng CI/CD](https://github.com/opencollab/arpack-ng/actions/workflows/jobs.yml/badge.svg)](https://github.com/opencollab/arpack-ng/actions/workflows/jobs.yml)
<a href="https://travis-ci.org/opencollab/arpack-ng"><img src="https://travis-ci.org/opencollab/arpack-ng.svg"/></a><br/>
[![Coverage Status](https://coveralls.io/repos/github/opencollab/arpack-ng/badge.svg?branch=master)](https://coveralls.io/github/opencollab/arpack-ng?branch=master)
ARPACK-NG is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.
| mandatory dependencies | optional dependencies | category |
|------------------------|---------------------------|---------------|
| BLAS, LAPACK | MPI, Eigen3, Boost.Python | LinearAlgebra |
Important Features:
## About the project
* Reverse Communication Interface.
* Single and Double Precision Real Arithmetic Versions for Symmetric,
Non-symmetric, Standard or Generalized Problems.
* Single and Double Precision Complex Arithmetic Versions for Standard or
Generalized Problems.
* Routines for Banded Matrices - Standard or Generalized Problems.
* Routines for The Singular Value Decomposition.
* Example driver routines that may be used as templates to implement numerous
Shift-Invert strategies for all problem types, data types and precision.
* arpackmm: utility to test arpack with matrix market files.
Note: to run this utility, you need the eigen library (to handle RCI).
* ILP64 support:
* Sequential arpack supports ILP64, but, parallel arpack doesn't.
* reminder: you can NOT mix ILP64 with LP64. If you compile arpack-ng with ILP64
(resp. LP64) support, you MUST insure your BLAS/LAPACK is compliant with ILP64
(resp. LP64).
* users: set INTERFACE64 at configure time.
* F77/F90 developers:
* all files which needs ILP64 support must include "arpackicb.h".
* when coding, use i_int (defined in arpackicb.h) instead of c_int.
i_int stands for "iso_c_binding int": it's #defined to c_int or c_int64_t
according to the architecture.
* C/C++ developers:
* all files which needs ILP64 support must include "arpackdef.h".
* when coding, use a_int (defined in arpackdef.h) instead of int.
a_int stands for "architecture int": it's #defined to int or int64_t according
to the architecture.
* example: to test arpack with sequential ILP64 MKL assuming you use gnu compilers
```$ ./bootstrap
$ export FFLAGS='-DMKL_ILP64 -I/usr/include/mkl'
$ export FCFLAGS='-DMKL_ILP64 -I/usr/include/mkl'
$ export LIBS='-Wl,--no-as-needed -L/usr/lib/x86_64-linux-gnu -lmkl_sequential -lmkl_core -lpthread -lm -ldl'
$ export INTERFACE64=1
$ ./configure --with-blas=mkl_gf_ilp64 --with-lapack=mkl_gf_ilp64
$ make all check```
* pyarpack: python support based on Boost.Python.Numpy exposing C++ API.
Check out ./EXAMPLES/PYARPACK/README for more details.
This project started as a joint project between Debian, Octave and Scilab in order to
provide a common and maintained version of arpack.
This project started as a joint project between Debian, Octave and Scilab in order to provide a common and maintained version of arpack.
This is now a community project maintained by a few volunteers.
Indeed, no single release has been published by Rice university for the last few years and since many software (Octave, Scilab, R, Matlab...)
forked it and implemented their own modifications, arpack-ng aims to tackle this by providing a common repository, maintained versions with a testsuite.
`arpack-ng` is replacing arpack almost everywhere.
Indeed, no single release has been published by Rice university for the last
few years and since many software (Octave, Scilab, R, Matlab...) forked it and
implemented their own modifications, arpack-ng aims to tackle this by providing
a common repository, maintained versions with a testsuite.
## Important Features
arpack-ng is replacing arpack almost everywhere.
- Reverse Communication Interface (RCI).
- Single and Double Precision Real Arithmetic Versions for Symmetric, Non-symmetric, Standard or Generalized Problems.
- Single and Double Precision Complex Arithmetic Versions for Standard or Generalized Problems.
- Routines for Banded Matrices - Standard or Generalized Problems.
- Routines for The Singular Value Decomposition.
- Example driver routines that may be used as templates to implement numerous
- Shift-Invert strategies for all problem types, data types and precision.
- `arpackmm`: utility to test arpack with matrix market files. Note: to run this utility, you need the eigen library (to handle RCI).
1. You have successfully unbundled ARPACK-NG and are now in the ARPACK-NG
directory that was created for you.
## Documentation
2. The directory SRC contains the top level routines including
the highest level reverse communication interface routines
Within DOCUMENTS directory there are three files for templates on how to invoke the computational modes of ARPACK.
* ssaupd, dsaupd - symmetric single and double precision
* snaupd, dnaupd - non-symmetric single and double precision
* cnaupd, znaupd - complex non-symmetric single and double precision
- ex-sym.doc
- ex-nonsym.doc and
- ex-complex.doc
The headers of these routines contain full documentation of calling
sequence and usage. Additional information is in the DOCUMENTS directory.
Also look in the README.MD file for explanations concerning the
other documents.
The directory PARPACK contains the Parallel ARPACK routines.
## ILP64 support
About ILP64 support:
3. Example driver programs that illustrate all the computational modes,
data types and precisions may be found in the EXAMPLES directory.
Upon executing the 'ls EXAMPLES' command you should see
- Sequential arpack supports [ILP64](https://www.intel.com/content/www/us/en/develop/documentation/onemkl-linux-developer-guide/top/linking-your-application-with-onemkl/linking-in-detail/linking-with-interface-libraries/using-the-ilp64-interface-vs-lp64-interface.html), but, parallel arpack doesn't.
- Reminder: you can NOT mix `ILP64` with `LP64`. If you compile `arpack-ng` with `ILP64` (resp. `LP64`) support, you MUST insure your BLAS/LAPACK is compliant with `ILP64` (resp. `LP64`).
- Set `INTERFACE64` at configure time.
* BAND
* COMPLEX
* NONSYM
* README
* SIMPLE
* SVD
* SYM
Note for F77/F90 developers:
Example programs for banded, complex, nonsymmetric, symmetric,
and singular value decomposition may be found in the directories
BAND, COMPLEX, NONSYM, SYM, SVD respectively. Look at the README
file for further information. To get started, get into the SIMPLE
directory to see example programs that illustrate the use of ARPACK in
the simplest modes of operation for the most commonly posed
standard eigenvalue problems.
- All files which needs `ILP64` support must include `"arpackicb.h"`.
- When coding, use `i_int` (defined in `arpackicb.h`) instead of `c_int`. `i_int` stands for `iso_c_binding int`: it's `#defined` to `c_int` or `c_int64_t` according to the architecture.
Note for C/C++ developers:
Example programs for Parallel ARPACK may be found in the directory
PARPACK/EXAMPLES. Look at the README file for further information.
- All files which needs `ILP64` support must include `"arpackdef.h"`.
- When coding, use `a_int` (defined in `arpackdef.h`) instead of `int`. Here, `a_int` stands for "architecture int": it's `#defined` to `int` or `int64_t` according to the architecture.
The following instructions explain how to make the ARPACK library.
**Example**: to test arpack with sequential `ILP64` MKL assuming you use gnu compilers
4. Unlike ARPACK, ARPACK-NG is providing autotools and cmake based build
system and iso_c_binding support (which enables to call fortran
subroutines natively from C or C++).
```bash
$ ./bootstrap
$ export FFLAGS='-DMKL_ILP64 -I/usr/include/mkl'
$ export FCFLAGS='-DMKL_ILP64 -I/usr/include/mkl'
$ export LIBS='-Wl,--no-as-needed -L/usr/lib/x86_64-linux-gnu -lmkl_sequential -lmkl_core -lpthread -lm -ldl'
$ export INTERFACE64=1
$ ./configure --with-blas=mkl_gf_ilp64 --with-lapack=mkl_gf_ilp64
$ make all check
```
Therefore, the classical commands should work as expected:
$ sh bootstrap
$ ./configure
$ make
$ make check
$ make install
## ISO_C_BINDING support
Furthermore, ARPACK-NG now provides CMake functionality:
$ mkdir build
$ cd build
$ cmake -D EXAMPLES=ON -D MPI=ON -D BUILD_SHARED_LIBS=ON ..
$ make
$ make install
builds everything including examples and parallel support (with MPI).
About ISO_C_BINDING support:
To use arpack from CMake, use ARPACK::ARPACK target:
- The install will now provide `arpack.h/hpp`, `parpack.h/hpp` and friends.
- Examples of use can be found in `./TESTS` and` ./PARPACK/TESTS/MPI`.
find_package(arpack-ng)
add_executable(main main.f)
target_include_directories(main PUBLIC ARPACK::ARPACK)
target_link_libraries(main ARPACK::ARPACK)
Those who are interested in `ISO_C_BINDING` support can checkout following links for more informations.
To use parpack from CMake, use PARPACK::PARPACK target:
- <http://fortranwiki.org/fortran/show/ISO_C_BINDING>
- <http://fortranwiki.org/fortran/show/Generating+C+Interfaces>
- <https://www.roguewave.com/sites/rw/files/attachments/StandardizedMixedLanguageProgrammingforCandFortran.pdf>
find_package(arpack-ng)
add_executable(main main.f)
target_include_directories(main PUBLIC PARPACK::PARPACK)
target_link_libraries(main PARPACK::PARPACK)
**Example**: to test arpack with ISO_C_BINDING
```bash
$ ./configure --enable-icb
$ cmake -D ICB=ON
```
## Eigen support
`arpack-ng` provides C++ eigensolver based on `eigen`.
Check out `./EXAMPLES/MATRIX_MARKET/README` for more details.
**Example**: to test arpack with `eigen`
```bash
$ mkdir build
$ cd build
$ cmake -D EXAMPLES=ON -D ICB=ON -D ICBEXMM=ON ..
$ make all check
```
## Python support
`pyarpack`: python support based on `Boost.Python.Numpy` exposing C++ API.
`pyarpack` exposes in python the `arpack-ng` C++ eigensolver (based on `eigen`).
Check out `./EXAMPLES/PYARPACK/README` for more details.
**Example**: to test arpack with python3
```bash
$ mkdir build
$ cd build
$ cmake -D EXAMPLES=ON -D ICB=ON -D ICBEXMM=ON -D PYTHON3=ON ..
$ make all check
```
## 📁 Directory structure
- You have successfully unbundled ARPACK-NG` and are now in the ARPACK-NG directory that was created for you.
- The directory SRC contains the top level routines including the highest level **reverse communication interface** routines
- `ssaupd`, `dsaupd`: symmetric single and double precision
- `snaupd`, `dnaupd`: non-symmetric single and double precision
- `cnaupd`, `znaupd`: complex non-symmetric single and double precision
- The headers of these routines contain full documentation of calling sequence and usage.
- Additional information is given in the `/DOCUMENTS` directory.
- The directory `PARPACK` contains the Parallel ARPACK routines.
- Example driver programs that illustrate all the computational modes, data types and precisions may be found in the EXAMPLES directory. Upon executing the `ls EXAMPLES` command you should see the following directories
```bash
├── BAND
├── COMPLEX
├── Makefile.am
├── MATRIX_MARKET
├── NONSYM
├── PYARPACK
├── README
├── SIMPLE
├── SVD
└── SYM
```
- Example programs for banded, complex, nonsymmetric, symmetric, and singular value decomposition may be found in the directories BAND, COMPLEX, NONSYM, SYM, SVD respectively.
- Look at the README file for further information.
- To get started, get into the SIMPLE directory to see example programs that illustrate the use of ARPACK in the simplest modes of operation for the most commonly posed standard eigenvalue problems.
> Example programs for Parallel ARPACK may be found in the directory `PARPACK/EXAMPLES`. Look at the README file for further information.
## Install 🚀
### Getting arpack-ng
Unlike ARPACK, ARPACK-NG is providing autotools and cmake based build system. In addition, `ARPACK-NG` also provides
`iso_c_binding` support, which enables to call fortran subroutines natively from C or C++.
First, obtain the source code 📥 from github:
```bash
$ git clone https://github.com/opencollab/arpack-ng.git
$ cd ./arpack-ng
```
If you prefer the ssh to obtain the source code, then use:
```bash
$ git clone git@github.com:opencollab/arpack-ng.git
$ cd ./arpack-ng
```
> Note, It is recommended to install `arpack` at standard location on your system by using your root privilege.
### Using autotools
In the source directory, use the following commands to configure, build and install `arpack-ng`.
```bash
$ sh bootstrap
$ ./configure --enable-mpi
$ make
$ make check
$ sudo make install
```
Congratulations 🎉, you have installed `arpack` lib using autotools (caution: you need `sudo` to install in your system).
The above-mentioned process will build everything including the examples and parallel support using MPI.
### Using cmake
You can install `ARPACK-NG` by using cmake. If you do not have cmake, then please download the binary from `pip` using:
```bash
$ python3 -m pip install cmake
$ which cmake && cmake --version
```
After installing cmake, follow the instruction given below.
Caution: Make sure you are in source directory of ARPACK-NG.
```bash
$ mkdir build
$ cd build
$ cmake -D EXAMPLES=ON -D MPI=ON -D BUILD_SHARED_LIBS=ON ..
$ make
$ sudo make install
```
✨ Congratulations, you have installed `arpack` lib using cmake (caution: you need `sudo` to install in your system).
The above-mentioned process will build everything including the examples and parallel support using MPI.
### Customize build / install
You can also customize the installation of `arpack` using the autotools.
To customize the install directories:
```bash
$ LIBSUFFIX="64" ./configure
$ make all install
```
To enable ILP64 support:
```bash
$ INTERFACE64="1" ITF64SUFFIX="ILP64" ./configure
$ make all install
```
To enable ISO_C_BINDING support:
```bash
$ ./configure --enable-icb
```
You can customize the build by declaring the cmake options during configuration.
To customize the install directories:
```bash
$ cmake -D LIBSUFFIX="64" ..
$ make all install
```
To enable ILP64 support:
```bash
$ cmake -D INTERFACE64=ON -D ITF64SUFFIX="ILP64" ..
$ make all install
```
To enable ISO_C_BINDING support:
```bash
$ cmake -D ICB=ON
```
## Supported Operating Systems:
### Linux support
`arpack-ng` runs on debian-based distros.
### Mac OS support
On mac OS, with GNU compilers, you may need to customize options:
$ LIBS="-framework Accelerate" FFLAGS="-ff2c -fno-second-underscore" FCFLAGS="-ff2c -fno-second-underscore" ./configure
```bash
$ LIBS="-framework Accelerate" FFLAGS="-ff2c -fno-second-underscore" FCFLAGS="-ff2c -fno-second-underscore" ./configure
```
To build with code coverage:
$ mkdir build
$ cd build
$ cmake -DCOVERALLS=ON -DCMAKE_BUILD_TYPE=Debug ..
$ make all check test coveralls
### Windows support
To get iso_c_binding support:
$ ./configure --enable-icb
$ cmake -D ICB=ON
The install will now provide arpack.h/hpp, parpack.h/hpp and friends.
Examples of use can be found in ./TESTS and ./PARPACK/TESTS/MPI.
A few related links can be found here:
`arpack-ng` runs on windows using `mingw64`.
* http://fortranwiki.org/fortran/show/ISO_C_BINDING
* http://fortranwiki.org/fortran/show/Generating+C+Interfaces
* https://www.roguewave.com/sites/rw/files/attachments/StandardizedMixedLanguageProgrammingforCandFortran.pdf
## Using arpack-ng from your own codebase
5. Within DOCUMENTS directory there are three files
### With autotools
* ex-sym.doc
* ex-nonsym.doc and
* ex-complex.doc
First, set `PKG_CONFIG_PATH` to the location in the installation directory where `arpack.pc` lies.
for templates on how to invoke the computational modes of ARPACK.
Also look in the README.MD file for explanations concerning the
other documents.
Custom installation examples:
$ LIBSUFFIX="64" ./configure; make all install
$ cmake -DLIBSUFFIX="64" ..; make all install
$ INTERFACE64="1" ITF64SUFFIX="ILP64" ./configure; make all install
$ cmake -DINTERFACE64=ON -DITF64SUFFIX="ILP64" ..; make all install
$ LIBSUFFIX="64" INTERFACE64="1" ITF64SUFFIX="ILP64" ./configure; make all install
$ cmake -DLIBSUFFIX="64" -DINTERFACE64=ON -DITF64SUFFIX="ILP64" ..; make all install
Then, insert the following lines in your `configure.ac`:
```
PKG_CHECK_MODULES([ARPACK], [arpack])
AC_SUBST([ARPACK_CFLAGS])
AC_SUBST([ARPACK_LIBS])
```
Note: make sure you have installed `pkg-config`.
### With CMake
You can use arpack in your CMake builds by using `ARPACK::ARPACK` target. For example,
```cmake
FIND_PACKAGE(arpack-ng)
ADD_EXECUTABLE(main main.f)
TARGET_INCLUDE_DIRECTORIES(main PUBLIC ARPACK::ARPACK)
TARGET_LINK_LIBRARIES(main ARPACK::ARPACK)
```
To use PARPACK in your Cmake builds, use `PARPACK::PARPACK` target:
```cmake
FIND_PACKAGE(arpack-ng)
ADD_EXECUTABLE(main main.f)
TARGET_INCLUDE_DIRECTORIES(main PUBLIC PARPACK::PARPACK)
TARGET_LINK_LIBRARIES(main PARPACK::PARPACK)
```
Note: Make sure to update `CMAKE_MODULE_PATH` env variable (otheriwse, `find_package` won't find arpack-ng cmake file).
## Using MKL instead of BLAS / LAPACK
How to use arpack-ng with Intel MKL:
* Let autotools/cmake find MKL for you based on pkg-config files (setting `PKG_CONFIG_PATH`) or cmake options (`BLA_VENDOR=Intel`).
* Refers to the Intel Link Advisor: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-link-line-advisor.html.
- Let autotools/cmake find MKL for you based on pkg-config files (setting `PKG_CONFIG_PATH`) or cmake options (`BLA_VENDOR=Intel`).
- Refers to the Intel Link Advisor: <https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-link-line-advisor.html>.
Good luck and enjoy.
## Good luck and enjoy 🎊