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Parallelized COVID19 Infection Simulation

Simulation for SIR (Susceptible, Infectious, Recovery) Model

Motivation

During the pandamic, there're an increasing demand on detecting and monitoring the infection simulation. However, simulation is a time-consuming and resource-intensive workload, which increases the burden for computing units these days. As a result, we comes up with a idea to use parallelism techniques to speedup the simulation process.

Our Implementation

In our work, we both optimize the calculating by employing two parallelism techniques: OpenMP & CUDA. In OpenMP Version, we proposed two ways: Blocked-Version and Row-Regioned-Version for parallelism. In CUDA Version, we proposed distance-based version.

You may find the more specific implementation details by reviewing our slides.

Installation & Execution

First of all, please make sure your environment has supported multi-threading and CUDA.

# Execute Sequential Version
make sequential
make run-seq

# Execute OpenMP Blocked Version
make omp-ver-block
make run-omp-ver-block

# Execute OpenMP Row Regioned Version
make omp-ver-region
make run-omp-ver-region

# Execute CUDA Distance Based Version
make cuda-v2
make run-cuda-v2

Contribution

Contributor:

  • Elven Lin
  • Mencher Chiang

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Parallelize Infectious Simulation of SIR Model on OpenMP & CUDA

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