Parallel solver of the Resource Constrained Project Scheduling Problem using CUDA platform.
License
CTU-IIG/RCPSPGpu
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
master
Could not load branches
Nothing to show
Could not load tags
Nothing to show
{{ refName }}
default
Name already in use
A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code
-
Clone
Use Git or checkout with SVN using the web URL.
Work fast with our official CLI. Learn more about the CLI.
- Open with GitHub Desktop
- Download ZIP
Sign In Required
Please sign in to use Codespaces.
Launching GitHub Desktop
If nothing happens, download GitHub Desktop and try again.
Launching GitHub Desktop
If nothing happens, download GitHub Desktop and try again.
Launching Xcode
If nothing happens, download Xcode and try again.
Launching Visual Studio Code
Your codespace will open once ready.
There was a problem preparing your codespace, please try again.
Latest commit
Git stats
Files
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
The program RCPSPSGpu is distributed under the terms of the GNU General Public License. Authors: Libor Bukata (bukatlib@fel.cvut.cz) and Premysl Sucha (suchap@fel.cvut.cz) Supported SW: GNU Compiler Collection (GCC), CUDA How to install: 1) If you would like to run bigger instances than J120, the following steps are necessary: a) make CreateHeaderFile b) ./CreateHeaderFile dataset_directory/*.sm (CudaConstants.h is updated) 2) Update the Makefile file: a) Set the CAPABILITY variable with respect to your graphics card architecture. b) Set installation path - variable INST_PATH. 3) Compile program: make all 4) Optional program installation (the program can be executed from the current directory): a) make install 5) Optional generation and installation of documentation to the Documentation/ directory: a) make doc For the information about program parameters run the command './RCPSPGpu --help'. You can download the standard datasets from http://www.om-db.wi.tum.de/psplib/. Remark: If you find this software useful for your research or you create an algorithm based on this software, please cite our original paper in your publication list. Libor Bukata, Premysl Sucha, Zdenek Hanzalek, Solving the Resource Constrained Project Scheduling Problem using the parallel Tabu Search designed for the CUDA platform, Journal of Parallel and Distributed Computing, Volume 77, March 2015, Pages 58-68, ISSN 0743-7315, http://dx.doi.org/10.1016/j.jpdc.2014.11.005.
About
Parallel solver of the Resource Constrained Project Scheduling Problem using CUDA platform.
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published