Parallel Computing with Python on a Raspberry Pi Cluster || OpenMPI and mpi4py install

Описание к видео Parallel Computing with Python on a Raspberry Pi Cluster || OpenMPI and mpi4py install

Today we are making a mini supercomputer! Not really, but sort-of, we are building a 4-node raspberry pi cluster. On this cluster we will be installing a package called OpenMPI which is a Message Passing Interface (MPI) critical for Parallel Computing. An MPI allows a complicated problem to be split into different processes and computed on separate processors, perhaps even on different nodes of a cluster.

In this tutorial, we will go through how to install OpenMPI, Python packages from source, and how we can use OpenMPI with Python using a module called mpi4py. This will enable us to use all nodes on our cluster to approximate pi ~3.14… We will be following three tutorials from Garrett Mills on Medium for installation on SLURM and enabling parallel computing using openMPI.

Building a raspberry pi cluster (Garrett Mills, 2018):   / building-a-raspberry-pi-cluster  

★ ★ QuantPy GitHub ★ ★
Collection of resources used on QuantPy YouTube channel. https://github.com/thequantpy

★ ★ Discord Community ★ ★
Join a small niche community of like-minded quants on discord.   / discord  

★ ★ Support our Patreon Community ★ ★
Get access to Jupyter Notebooks that can run in the browser without downloading python.
  / quantpy  

★ ★ ThetaData API ★ ★
ThetaData's API provides both realtime and historical options data for end-of-day, and intraday trades and quotes. Use coupon 'QPY1' to receive 20% off on your first month.
https://www.thetadata.net/

★ ★ Online Quant Tutorials ★ ★
WEBSITE: https://quantpy.com.au

★ ★ Contact Us ★ ★
EMAIL: [email protected]

Disclaimer: All ideas, opinions, recommendations and/or forecasts, expressed or implied in this content, are for informational and educational purposes only and should not be construed as financial product advice or an inducement or instruction to invest, trade, and/or speculate in the markets. Any action or refraining from action; investments, trades, and/or speculations made in light of the ideas, opinions, and/or forecasts, expressed or implied in this content, are committed at your own risk an consequence, financial or otherwise. As an affiliate of ThetaData, QuantPy Pty Ltd is compensated for any purchases made through the link provided in this description.

Комментарии

Информация по комментариям в разработке