Gain insights into using HPC systems and supercomputers to solve large computational problems. Explore HPC components, software stacks, job schedulers, and parallel programming, including Open MP, MPI, and GPU coding.

Learn to use High Performance Computing (HPC) Systems  and solve large computational problems.  This course assumes basic familiarity with the Bash command line environment found on GNU/Linux and other Unix-like environments. This course is of the first of its kind, should be your second step from my previous Educative course "Learn to Analyze Text Data in Bash Shell and Linux"

You'll learn:
- Intro to HPC Systems and Supercomputers
- HPC system's basic components
- HPC software stack
- HPC job schedulers and batch systems (PBS and Slurm with demos)
- Introduction to parallel programming (Open MP, MPI and GPU coding)

Video demos are included, I think it is a must have course for students, researchers, big data analysts, and developers. It will help you to utilize High Performance Computing systems at your institution. Non-interactive course. More details at:  www.scientificprogramming.io/learn-hpc

Ajay Shenoy

This course demystifies HPC and introduces you to the essential tools required to schedule and run parallel programs. Easy to understand.

India

Learn to Use HPC Systems and Supercomputers

The term **GPU** was popularized by nVIDIA in 1999, who marketed a computer graphics
card called GeForce 256 as “The world’s first GPU”. However, the card was mainly designed
for rendering of high-end computer graphics and enhancing computer-based gaming performance.
In contrast, today’s GPUs also provide an inexpensive platform for developing and
executing high-performance non-graphical applications. The development of general-purpose
applications on GPUs is often termed as **GPGPU (General Purpose Computing on GPUs)** and
a number companies have started to produce GPUs that are capable of general purpose computation.

Among the various kinds of GPUs, we have specifically chosen nVIDIA’s **Tesla** is a popular development
platform, however latest GPUs like **Fermi K80, Pascal, Volta** are also not very different in terms of basics. All these devices allow programmers to develop applications using an easily programmable C-like language, called **Compute
Unified Device Architecture (CUDA)**.



Supercomputers and HPC clusters

Components of a HPC system

HPC software stack

PBS - Portable Batch System

SLURM -Workload Manager

Parallel programming - OpenMP

Parallel programming - MPI

Parallel programming - GPU and CUDA

Conclusions and references

GPUs - graphics processing units