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

**OpenMP** (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared memory multiprocessing programming in `C`, `C++`, and `Fortran`. It consists of a set of **compiler directives**, **library routines**, and **environment variables** that influence the code's run-time behavior.

OpenMP uses a portable, scalable model that gives programmers a simple and flexible interface for developing parallel applications for platforms ranging from the standard desktop computer to the **supercomputer**.

An application built with the hybrid model of parallel programming can run on a computer cluster using both **OpenMP** and **Message Passing Interface (MPI)**, such that OpenMP is used for parallelism within a (multi-core) node while MPI is used for parallelism between nodes. 

### History 

OpenMP is managed by the nonprofit technology consortium OpenMP Architecture Review Board (or OpenMP ARB), jointly defined by a group of major computer hardware and software vendors. They publised its first API specifications in October 1997. The latest version  specification (4.5) released in 2015 adds/ improves supports for **accelerators**, **atomics**, **error handling**, **thread affinity**, **tasking extensions**, **user defined reduction**, **SIMD support**, and so on.

### Getting the OpenMP

All the latest OpenMP versions are integrated with the recent GNU compilers (`4.9` and above), no need to install them separately!



**OpenMP** (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared memory multiprocessing programming in `C`, `C++`, and `Fortran`. It consists of a set of **compiler directives**, **library routines**, and **environment variables** that influence the code's run-time behavior.

OpenMP uses a portable, scalable model that gives programmers a simple and flexible interface for developing parallel applications for platforms ranging from the standard desktop computer to the **supercomputer**.

An application built with the hybrid model of parallel programming can run on a computer cluster using both **OpenMP** and **Message Passing Interface (MPI)**, such that OpenMP is used for parallelism within a (multi-core) node while MPI is used for parallelism between nodes. 

# History 

OpenMP is managed by the nonprofit technology consortium OpenMP Architecture Review Board (or OpenMP ARB), jointly defined by a group of major computer hardware and software vendors. They publised its first API specifications in October 1997. The latest version  specification (4.5) released in 2015 adds/ improves supports for **accelerators**, **atomics**, **error handling**, **thread affinity**, **tasking extensions**, **user defined reduction**, **SIMD support**, and so on.

# Getting the OpenMP

All the latest OpenMP versions are integrated with the recent GNU compilers (`4.9` and above), no need to install them separately!



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

OpenMP