Duplex is a high-performance global optimization algorithm for nonconvex, nonlinear, and functional optimization problems. The following core capabilities are included:
- Duplex can find global optimum of nonlinear non-convex functions.
- Duplex implements variety of gradient-descent based optimizations internally, such as Momentum, AdaDelta, Adamax. Duplex can also optimize when the gradient information are not available.
- Duplex supports unsupervised learning algoriths for clustering.
- If the gradient information are not available (for circuit optimization), duplex uses reinforcement learning to predict the landscape of energy function.
- Duplex supports Synopsys HSPICE for solving nonlinear systems.
The latest release and a complete manual may be found at the Duplex home page: http://adel.ac/duplex
Duplex requires the following dependencies to be installed:
- Eigen 3.3.0 linear algebra library. Install eigen using
brew install eigen
- Boost 1.51 Duplex requires both headers and compiled binaries. Install using
brew install boost
- Config4cpp configuration library. The binaries for the config4cpp for macOS are already shipped with Duplex (
- Pangolin for plotting and managing display. The Pangolin will replace the gnuPlot. Duplex will install Pangolin as a submodule in
- GnuPlot for drawing plots (Optional). Install gnuplot using
brew install gnuplot
Duplex uses CMake as a build system.
git clone git://github.com/ahmadyan/Duplex cd Duplex mkdir build cd build cmake .. make
cmake .. -GXcode to generate the xcode project file (or other generators).
Few examples are provided in
/bin directory. Few MATLAB tests are available in the
- ./duplex --config example.cfg
- Currently the duplex binaries and the configurations has to be in the same directory, so please output the binary in the bin folder.
- Example configuration files are available in the /bin directory
- If using hspice as a numerical simulator, User should set an environment variable DUPLEX_SIM_ID to an integer value. If you don't want to set the environment variable, run Duplex from the python wrapper (test/duplex.py) in test directory. Python wrapper requires Python 3+.
Duplex uses llvm coding style. Any PR will be formatted using clang-format.