Nano

In the last article, I discussed the architecture of the HPC. If you have not read that article, I would recommend that you read it before proceeding with this one. Architecture of High-Performance Computing Server at BIT Mesra  The power of HPC can be utilized for its most important application in the field of computer science: Machine Learning. I am assuming that you already have obtained your SSH credentials to log on to the master node. Also, we will be setting up the environment in Python. Let's jump straight to the steps. How To? Step 1: Download and Install Anaconda on the Master Node Note that you are not the root user of the HPC. You are just a regular user, and therefore, administrative commands (such as sudo or su) will not work. Anaconda has made it much easier to install Python packages for non-root users, and we will be using Anaconda for setting up Python 3 and installing the required packages. Log in to the master node     > ssh be1005815@172.16.23.1 Go...

A High-Performance Computing (HPC) server was installed a few years back. It was a replacement for PARAM 10000, the supercomputer that is no longer available for use. Initially, the HPC was under the Department of Computer Science. The Department of Chemical Engineering and Biotechnology was the primary user of the HPC (mostly for simulation purposes), and so the administration decided to move it under the Central Instrumentation Facility (CIF). You need permission from the CIF to access the HPC. HPC is only available for research purposes, and you need to provide a good reason along with a proper recommendation from a professor to gain access to the HPC. The HPC is at least 20 times more powerful than the most powerful PC that anyone has on campus. Also, I recently checked the usage and realized that not even 10% of its power is being utilized. I hope this blog post will help you in understanding the core architecture of the HPC. Architecture The Architecture of High Performance Compu...