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Broadcast Communication in MPI

Broadcast Communication in MPI

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In MPI (Message Passing Interface), broadcast communication is a fundamental operation that allows one process to efficiently send data to all other processes in a communicator. This means that a single piece of data is sent from one process, often referred to as the “root” process, to all other processes within the MPI environment. Broadcast communication is particularly useful for distributing global information or settings to all participating processes. How Broadcast Communication Works In MPI, broadcast communication works by having…

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Monte Carlo Simulation: MPI4Py

Monte Carlo Simulation: MPI4Py

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Monte Carlo simulations are a statistical technique that allows for solving problems through random sampling. They are widely used in various fields such as physics, finance, and engineering to understand the impact of risk and uncertainty in prediction and forecasting models. The core idea is to use randomness to solve problems that might be deterministic in nature. You can visit the detailed tutorial here. For example, to estimate the value of Pi ((\pi)), we can use the Monte Carlo method….

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MPI: Concurrent File I/O for by Multiple Processes

MPI: Concurrent File I/O for by Multiple Processes

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In this tutorial, we’ll explore an MPI (Message Passing Interface) program using mpi4py to demonstrate how multiple processors can collectively write to and read from a shared file. The detailed tutorial of MPI with a python can be visited here. Code Code Explanation Imports the necessary MPI module from mpi4py which provides bindings for MPI functionality in Python. Initializes MPI communication (comm) for all processes (MPI.COMM_WORLD). rank is assigned the unique identifier (rank) of the current process, and size represents…

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MPI Gather Function in Python

MPI Gather Function in Python

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The gather function is used to gather data from multiple processes into a single process. We’ll go through the provided code, line by line, and understand how the gather function works. The detailed tutorial of MPI with a python can be visited here. Code Explanation This line imports the MPI functionality from the mpi4py library. These lines initialize the MPI communicator (comm) and obtain the total number of processes (size) and the rank of the current process (rank). Each process…

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