This project focuses on developing a parallelized population simulation to study the dynamics of disease transmission within an environment by leveraging CPU and GPU parallelism, thread processing control, and inter-process communication techniques. The goal is to create a computationally efficient representation of a pandemic.
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This project focuses on developing a parallelized population simulation to study the dynamics of disease transmission within an environment by leveraging CPU and GPU parallelism, thread processing control, and inter-process communication techniques. The goal is to create a computationally efficient representation of a pandemic.
malikendsley/parallel-disease-simulation
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This project focuses on developing a parallelized population simulation to study the dynamics of disease transmission within an environment by leveraging CPU and GPU parallelism, thread processing control, and inter-process communication techniques. The goal is to create a computationally efficient representation of a pandemic.
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- C++ 75.3%
- Jupyter Notebook 15.9%
- Cuda 7.9%
- Python 0.5%
- C 0.3%
- CMake 0.1%