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This release is a pre-release and may not be stable for production use.

Rapid Optimization Library (ROL)

Rapid Optimization Library

ROL (as in rock and roll) is a high-performance C++ library for numerical optimization. ROL brings an extensive collection of state-of-the-art optimization algorithms to virtually any application. Its programming interface supports any computational hardware, including heterogeneous many-core systems with digital and analog accelerators. ROL has been used with great success for optimal control, optimal design, inverse problems, image processing and mesh optimization, in application areas including geophysics, structural dynamics, fluid dynamics, electromagnetics, quantum computing, hypersonics and geospatial imaging.

For additional details, see https://rol.sandia.gov.

Feature highlights:

  1. Vector abstractions and matrix-free interface for universal applicability
  2. Modern algorithms for unconstrained and constrained optimization
  3. Easy-to-use methods for stochastic and risk-aware optimization
  4. Fast and robust algorithms for nonsmooth optimization
  5. Trust-region methods for inexact and adaptive computations
  6. PDE-OPT application development kit for PDE-constrained optimization
  7. Interfaces and algorithms for optimal experimental design

Getting Started

ROL is a C++ library with a cmake build system. There are minimal third-party library requirements consisting of BLAS and LAPACK which also require a suitable Fortran compiler on the system. On Linux-based systems with an apt package manager, the dependencies may be installed with

apt install cmake gfortran libopenblas-dev liblapack3

Some typical configure scripts may be found in the .github/workflows/ directory. An in-source release build including ROL's examples and tests may be configured from within the source directory with

cmake -D CMAKE_BUILD_TYPE:STRING=RELEASE \
      -D ENABLE_EXAMPLES:BOOL=ON \
      -D ENABLE_TESTS:BOOL=ON \
      -B build \
      -D CMAKE_INSTALL_PREFIX=build/install \
      .

After a successful configure, ROL is built by then changing to the build directory and running make

cd build
make

One can then install it

make install

Building against ROL

Assuming we have a directory called 'roltest' which contains files we would like to run using ROL. In /dir/to/roltest, create a CMakeLists.txt with the following:

cmake_minimum_required(VERSION 3.10)  
project(test)
set(CMAKE_CXX_STANDARD 17) 

enable_language(C)
enable_language(CXX)

message(STATUS "ROL directory is: ${ROL_DIR}/include")
include_directories("${ROL_DIR}/include") #one down for all files
find_library(ROL_LIB NAMES rol librol PATHS ${ROL_DIR}/lib NO_DEFAULT_PATH)
if(ROL_LIB)
  message(STATUS "We found ROL!")
else()
  message(FATAL_ERROR "ROL library not found!")
endif()

add_library(rol::rol UNKNOWN IMPORTED)
set_target_properties(rol::rol PROPERTIES IMPORTED_LOCATION "${ROL_LIB}")
add_executable(ROLtest mytest.cpp)
target_link_libraries(ROLtest PRIVATE rol::rol) 

add_executable(ROLtest mytest.cpp)

The file in mytest then simply tests that it can find a basic ROL type:

#include "ROL_StdVector.hpp"
typedef double RealT;

int main() {
  int dim = 100; 

  ROL::StdVector<RealT> x(dim);
  x.randomize(-1.0, 1.0);
  std::cout << "What's the norm of x? " << x.norm() << std::endl;
}

Compiling and executing should then be a matter of:

$ cmake . -DROL_DIR=/Users/../path/to/rol/build/install
$ make
$ ./ROLtest
What's the norm of x? "some random number"

Python Interface

The python pip package rol-python is the official python interface to ROL. It is available at https://pypi.org/project/rol-python/ and can be installed via

pip install rol-python

See COPYRIGHT and LICENSE.

Questions?

Contact team or developers:

Metadata

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rol_python-2026.8.28.dev1935-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.14 CPython 3.14 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
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A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

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