mtanneau / pips Goto Github PK
View Code? Open in Web Editor NEWThis project forked from drehfeldt/pips
Parallel solvers for optimization problems
License: Other
This project forked from drehfeldt/pips
Parallel solvers for optimization problems
License: Other
PIPS - suite of parallel optimization solvers mainly for stochastic optimization problems consisting of the following solvers: i. PIPS-IPM - parallel MPI+OpenMP interior-point for stochastic LPs and convex QPs ii. PIPS-S - parallel MPI implementation of the revised simplex method iii. PIPS-NLP - parallel MPI interior-point for structured NLPs ################################################################################### # LICENSE ################################################################################### See LICENSE file. #################################################################################### # CONTRIBUTIONS #################################################################################### PIPS-IPM Developed by: Cosmin G. Petra - Lawrence Livermore / Argonne National Laboratory Contributions from: Miles Lubin - Argonne National Laboratory Naiyuan Chiang - Argonne National Laboratory PIPS-S Developed by: Miles Lubin - Argonne National Laboratory Cosmin G. Petra - Lawrence Livermore / Argonne National Laboratory Contributions from: Geoffrey Oxberry - Lawrence Livermore National Laboratory Julian Hall - U. of Edinburgh PIPS-NLP Developed by: Naiyuan Chiang - Argonne National Laboratory Victor Zavala - Argonne National Laboratory and Univ. of Wisconsin-Madison Cosmin G. Petra - Lawrence Livermore / Argonne National Laboratory #################################################################################### # INSTALATION Instructions #################################################################################### Building PIPS-S only can be achieved via 1) cmake -DBUILD_ALL=OFF -DBUILD_PIPS_S=ON <path_to_CMakeLists.txt> or 2) including "set(BUILD_ALL OFF); set(BUILD_PIPS_S ON)" in a toolchain file, then invoking cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_toolchain_file> <path_to_CMakeLists.txt> Same applies to PIPS-IPM and PIPS-NLP (option names BUILD_PIPS_IPM and BUILD_PIPS_NLP, respectively). General instalation instructions 1. Install package wget, cmake, mpich2, and boost. You can get them via the following command (xxx stands for the name of the package): In Linux(Ubuntu): apt-get install xxxx 2. Go to the following folders and run the script wgetXXX.sh ThirdPartyLibs/ASL ThirdPartyLibs/CBC ThirdPartyLibs/ConicBundle ThirdPartyLibs/METIS For an example, use command "sh wgetASL.sh" in the folder ThirdPartyLibs/ASL 3. Download MA27 and MA57 from HSL and put the source code in the correct folder. (See ThirdPartyLibs/MA27/README.txt and ThirdPartyLibs/MA57/README.txt for more details.) 4. Assuming we are trying to install PIPS in the folder PIPSMAINPATH/build_pips, where PIPSMAINPATH is the root instalation folder, use the following commands in the PIPSMAINPATH folder to configure and install PIPS: mkdir build_pips cd build_pips cmake .. make 5. The build system will install executables from three sources: PIPS-IPM, PIPS-S and PIPS-NLP. ##################################################################################### # ACKNOWLEDGMENTS ##################################################################################### PIPS has been developed under the financial support of: - Department of Energy, Office of Advanced Scientific Computing Research - Department of Energy, Early Career Program - Department of Energy, Office of Electricity Delivery and Energy Reliability PIPS-IPM and PIPS-NLP are derivative works of OOQP (http://pages.cs.wisc.edu/~swright/ooqp/) by E. Michael Gertz and Stephen. Wright
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.