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PhysiCell-X constitutes a new development branch created from the original PhysiCell tool, whose objective focuses on expanding its capabilities to use distributed computing. This approach allows the tool to run simultaneously on different nodes, and therefore, being able to combine their resources as a single machine, which is crucial for simulating biological scenarios where memory requirements exceed the available capacity of the individual machines. To this end, PhysiCell-X extends the official OpenMP-based version to an OpenMP + MPI (Message Passing Interface) solution, where MPI provides the particular mechanism to efficiently distribute the computational load between the different connected nodes. Hence, users could expand their cellular simulations to include a larger number of cells, substrates or molecular pathways.
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PhysiCell-X constitutes a new development branch created from the original PhysiCell tool, whose objective focuses on expanding its capabilities to use distributed computing. This approach allows the tool to run simultaneously on different nodes, and therefore, being able to combine their resources as a single machine, which is crucial for simulating biological scenarios where memory requirements exceed the available capacity of the individual machines. To this end, PhysiCell-X extends the official OpenMP-based version to an OpenMP + MPI (Message Passing Interface) solution, where MPI provides the particular mechanism to efficiently distribute the computational load between the different connected nodes. Hence, users could expand their cellular simulations to include a larger number of cells, substrates or molecular pathways.
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In this tutorial, we will explore PhysiCell-X’s capabilities to run simulations in parallel. In particular, we will leverage the different cores that a single machine could have, and subsequently, the different nodes available at a supercomputer such as MN4.
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In this tutorial, we will explore PhysiCell-X’s capabilities to run simulations in parallel. In particular, we will leverage the different cores that a single machine could have, and subsequently, the different nodes available at a supercomputer such as MN4.
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