Summary of the Project

This project is a demonstrator for the use of distributed computing for physics simulations by connecting four Jetson Nano devices via a network switch and leveraging Dask to distribute computational loads.

Two simulations were implemented:

1. 2D Ising Model: The simulation models the evolution of a spin lattice using the Metropolis algorithm, where multiple grids are distributed across multiple computing nodes, enabling parallel updates.
2. 1D Particle Chain: A thermodynamic simulation of a 1D chain of particles, where various physical properties (e.g., energy, temperature) are computed, by simulating a huge chain with smaller parallel subchains.

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Methods Used

Hardware & Software

• Hardware: Four Jetson Nano boards connected through a switch.
• Software: Dask for parallel computing, NumPy for numerical operations.

Parallelization with Dask

• Client-Worker Setup: Dask's distributed scheduler was used, with Jetson Nanos acting as worker nodes.
• Task Distribution: The computational load is split among nodes, each handling part of the evolution.
• Data Management: Dask arrays were used to manage distributed data efficiently.

2D Ising Model Simulation

• Implemented using the Metropolis algorithm to model spin state changes.
• The grid was copied 10 times, each processed independently in parallel.
• The lowest energy update gets picked at each step allowing for faster convergence time.

1D Particle Chain Simulation

• The system modeled interactions between particles using thermodynamic principles.
• Dask was used to distribute the calculations across multiple nodes by splitting the 1D chain into multiple sub-chains.
• Energy, and other thermodynamic quantities were computed.

Limitations

• Edge devices are not apropriate for this task due to memory limitations.
• Nevertheless this was a demo project to grasp the pronciplesof distributed computing.