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Architecture of High Performance Computing Server at BIT Mesra

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...

Setting up Machine Learning Environment on High Performance Computing Server

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...

Rendering Performance Evaluation - Android SDK vs React Native

UI rendering speed has always been a key factor in evaluating a new technology. The lower the rendering time, the more preferable the technology. In recent times, React Native has become very popular for developing native apps. Such apps are truly native and significantly different from other similar technologies like Xamarin and Cordova. I recently had some time to evaluate how React Native compares to the Android SDK. TLDR : As you might expect, the Android SDK outperforms React Native by a significant margin. However, React Native technology is slowly catching up (most of the credit goes to the amazing diff rendering technology, which forms the core of React). React Native is efficient enough for apps with a small number of UI components that can be rendered within a reasonable time. Performance Comparison Emulator Model - Google Pixel 2 API Level - 24 Resolution - 1080 x 1920 (420 dpi) CPU - x86 Target - Android 7.0 RAM - 1536 MB Evaluation Criteria We will be creating a large numb...

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