https://github.com/ktaletsk/gpu_dsm
🔗Accessible quantitative polymer rheology predictions with slip-links on GPU
https://github.com/ktaletsk/gpu_dsm
c-plus-plus cuda gpu polymer rheology
Last synced: 9 months ago
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🔗Accessible quantitative polymer rheology predictions with slip-links on GPU
- Host: GitHub
- URL: https://github.com/ktaletsk/gpu_dsm
- Owner: ktaletsk
- License: gpl-3.0
- Created: 2014-09-19T16:24:56.000Z (almost 12 years ago)
- Default Branch: master
- Last Pushed: 2020-03-27T17:23:12.000Z (about 6 years ago)
- Last Synced: 2024-08-21T19:32:14.465Z (almost 2 years ago)
- Topics: c-plus-plus, cuda, gpu, polymer, rheology
- Language: C++
- Homepage: http://www.chbe.iit.edu/~schieber/
- Size: 2.65 MB
- Stars: 7
- Watchers: 5
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: License.md
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README
### **The Discrete Slip-Link Model (DSM)** is a mathematical model that describes the dynamics of flexible entangled polymer melts.
**GPU DSM** is a computational implementation of that model on CUDA/C++. GPU DSM is developed in [The Center for molecular study of condensed soft matter (μCoSM)](http://www.chbe.iit.edu/~schieber/index.html). GPU DSM is free open-source software under the GNU GPL v3.0 license.
**[Download latest Linux GUI version](https://github.com/ktaletsk/gpu_dsm/releases)**
### Compilation instructions:
#### Linux (tested on Ubuntu/Kubuntu 14.04)
Requirements:
g++
**[Cuda Toolkit](https://developer.nvidia.com/cuda-toolkit)** (6.0, 6.5, 7.0, 7.5, 8.0, 9.0, 9.1)
**[Qt](http://www.qt.io/download-open-source/)** (for GUI)
optional: make
1. Open terminal.
2a. Compile the command line interface (CLI) version, navigate to the directory where you extracted the zip file:
`cd /gpu_dsm/CLI`.
2b. Compile the graphical user interface (GUI) version, navigate to the directory where you extracted the zip file:
`cd /gpu_dsm/GUI`.
3a. Run `make all` to complie **gpu_DSM**.
3b. Run `//gcc_64/bin/qmake -spec linux-g++ -o Makefile dsm.pro`. Current version of Qt is 5.6.
Run `make all` to compile **dsm**.
4a. You can test it by running `./gpu_DSM`.
4b. You can test it by running `./dsm` or clicking to the app icon in a file manager.
#### Windows (tested on Windows 10, 64bit)
Requirements:
**[Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/)** (Community/Professional/Enterprise)
**[CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit)**
0. Install Visual Studio first, then install CUDA.
1. Open x64 Native Tools Command Prompt for VS 2017.
2. Move to `/gpu_dsm/CLI`.
3. Compile code using `make.bat` command. Make sure to change `-gencode arch=compute_50,code=sm_50` to reflect appropriate compute capability of your Nvidia GPU. To find compute capability of your GPU check [this page](https://developer.nvidia.com/cuda-gpus). For example, NVIDIA TITAN X has compute capability 6.1 and you will need to change the command flag to `-gencode arch=compute_61,code=sm_61`.
4. You can test it by running `gpu_DSM.exe`.
#### Running (CLI):
**gpu_DSM** command line parameters:
first parameter is seed/job_ID
example:
`./gpu_DSM 1`
all the files generated in this run will have "_1" in the filename.
additionally 1 will be used as a seed number for pseudo random number generator
-s filename
saves chain conformations in "filename" file in the end of run.
-l filename
loads previously saved chain conformations from the "filename" file in the beginning of run.
-d number
selects GPU to use. Useful if multiple GPU are present in the system. Numberring starts from 0.
-distr
saves final Z,N,Q distributions in .dat files
### Citation
[](https://zenodo.org/badge/latestdoi/24236916)