Computer Science

This is not a technical write up. This is a story that I want to share which might be a lesson for several Web & App developers out there. Bitotsav is the annual cultural fest of BIT Mesra and the Tech Team was responsible for developing the Website and the Android App. There were 46 events in the fest and we were responsible for sending out updates (announcements, results, etc.) for each event to the app. 16th February 2019, on the 2nd day of the fest, the website started experiencing problems. The website got slower and slower. The website was hosted on Microsoft Azure Virtual Machine. It was evening around at 5:00 PM. I checked the logs for the Virtual Machine. In the past 6 hours, 700 GB of data was uploaded and downloaded from the server. The Virtual Machine had 4 VCPUs and all of them were being rigorously used. Due to such huge traffic, all the APIs stopped responding. The app was no longer usable. No updates could be sent to the participants. What was happening? In the

In the last article, I had discussed the architecture of the HPC. In case you have not read the article, I would recommend you to read it before moving on to this article. 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 got your SSH credentials to log on to the master node. Also, we will be setting up the environment in Python. Lets jump straight to the steps. Step 1: Download and Install Anaconda on the master node Note that you are not the root user of HPC. You are just a regular user and so administrative commands (sudo or su) won't 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 required packages. Login to the master node.     > ssh be1005815@172.16.23.1 Go to  https://www.ana

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