- Connect to the Bessemer HPC system and login
- Run the command
git clone https://github.com/MILeach/TB_Model.git
to copy the project files into your user area. - Run
cd TB_Model
to move into the project directory - Run
sbatch build.sh
to submit an HPC job which will build the project
Requirements for building locally
- Nvidia graphics card
- A valid CUDA installation
Build Instructions
- Open a terminal and navigate to the folder where you wish to set up the project
- Run the command
git clone https://github.com/MILeach/TB_Model.git
to copy the project files into your user area. - Run
cd TB_Model/FLAMEGPU/examples/TB_Model
to move into the project directory - Run
make
to build the project
- Navigate to the
TB_Model/FLAMEGPU/examples/TB_Model/initializer
folder - Modify histo.csv to adjust the number of people in each sex/age category
- run
python3 preprocess.py data.in
to generate the data.in file which describes the population - For an HPC build, copy the created
data.in
file to theTB_Model/input
folder. For a local build, copy the file to theTB_Model/FLAMEGPU/examples/TB_Model/input
folder. - For an HPC build, create a folder inside the
TB_Model/input
folder and copy thenetwork.json
file into it. - Parameters are controlled using the FLAMEGPU XML input files. For an HPC build, place any FLAMEGPU XML input files you wish to run together in a folder in the
TB_Model/input
directory. For a local build, place your FLAMEGPU XML input file in theTB_Model/FLAMEGPU/examples/TB_Model/iterations
folder.
- Navigate to the top level
TB_Model
directory - Ensure the
input
folder contains the correctdata.in
file and a folder containing a copy ofnetwork.json
and the XML input files you wish to run as described in the Setting up the Model section - Run the command
sbatch run.sh input_folder_name number_of_iterations
whereinput_folder_name
is the name of the folder that contains the XML files andnumber_of_iterations
is the number of timesteps you wish to run the simulation for - When the job is completed, the output files should be available in the
output
folder
- Navigate to the
TB_Model/FLAMEGPU/examples/TB_Model
directory - Ensure the XML input file,
network.json
file anddata.in
file are present in the iterations folder - Run the command
./bin/linux-x64/Release_Console/Project iterations/input_filename.xml number_of_iterations XML_output_frequency 0
sacct -v
- lists your active jobsscancel job_number
- cancels the job with id job_number