OpenHPC is a set of community driven FOSS tools for Linux based HPC. OpenHPC does not have specific hardware requirements. [2]
| OpenHPC | |
|---|---|
 | |
| Initial release | November 12, 2015 [1] |
| Stable release | 2.4 (November 16, 2021) [±] |
| Repository | https://github.com/openhpc |
| Operating system | CentOS, SUSE Linux Enterprise Server |
| Platform | x86_64, aarch64 |
| Type | Cluster software |
| License | Free software (Apache_License and other licenses) |
| Website | openhpc |
History
A birds-of-a-feather panel discussion titled "Community Supported HPC Repository & Management Framework" convened at the 2015 edition of the International Supercomputing Conference. The panel discussed the common software components necessary to build linux compute clusters and solicited feedback on community interest in such a project.[3] Following the response, the OpenHPC project was announced at SC 2015 under the auspices of the Linux Foundation. [4][5]
Releases
| Version | Date |
|---|---|
| 1.3.3 | November 08, 2017 |
| 1.3.2 | September 07, 2017 |
| 1.3.1 | June 16, 2017 |
| 1.3 | March 31, 2017 |
| 1.2.1 | January 24, 2017 |
| 1.2 | November 12, 2016 |
| 1.1.1 | June 21, 2016 |
| 1.1 | April 18, 2016 |
| 1.0.1 | February 05, 2016 |
| 1.0 | November 12, 2015 |
Type of applications and different type of purposes
The term "advanced parallel computing" refers to any calculation that requires more than one computer for its purpose, or, in other words, simultaneously uses multiple computers. Super computers and computer clusters are used to solve a bunch of complex equations. The main applications are: - Data analysis and maintenance - simulation - modeling - Software development - View massively interdependent data - Quick Math Calculations. HPC is used for the following purposes: - Developing products and refining them - Optimization of production and its processes - Analysis or mass development of data - Leading extensive research projects - Storage of large amounts of data for later analysis - Productivity consumption, search and modeling - Computer imaging to explain the research results - Simulation and modeling of complex processes. Computational science along with computing resources and HPC technology are the three pillars to replicate theories and theories with the results of practical experiments. HPC is capable of working with huge amounts of data and analyzing results very quickly. This can take several months with conventional computers, while HPC computers can be run in just a few minutes or hours. It should be noted that in many cases ordinary computers are basically impossible to perform such calculations. Using HPC saves you time and money, and allows you to simulate and see what's happening in reality without using prototypes, analyze, analyze weaknesses And measure strength, correct defects and errors, design two times and see the result. This is a virtual reality that collects all human scientific knowledge today in the form of a software that itself is the invention of man. The software, with millions and even billions calculated on the data and analyzing all the initial results and millions of times, are able to give us a final result as an output. Put up Of course, all of these computational operations are beyond the power of the human mind, but there is a solution, and it is the advanced computer systems, super computers, or systems based on the parallel processing of HPC data. Some of the many examples of HPC capabilities include computational fluids dynamics, oil operations, car accident test simulations, air flow dynamics on aircraft wings, data storage, graphic animations, illustration and modeling of face reconstruction.
Design
OpenHPC provides an integrated and tested collection of software components that, along with a supported standard Linux distribution, can be used to implement a full-featured compute cluster. Components span the entire HPC software ecosystem including provisioning and system administration tools, resource management, I/O services, development tools, numerical libraries, and performance analysis tools. The architecture of OpenHPC is intentionally modular to allow end users to pick and choose from the provided components, as well as to foster a community of open contribution.[7] The project provides recipes for building clusters using CentOS (v7.4) and SUSE Linux Enterprise Server (v12sp3) on x86_64 as well as aarch64 architectures.[8]
See also
References
- ^ v1.0.GA
- ^ Project charter at Linuxfoundation
- ^ ISC 2015 - Community Supported HPC Repository & Management Framework
- ^ InsideHPC -- Linux Foundation Announces OpenHPC Collaborative Project
- ^ Linux Foundation - High Performance Computing Leaders Unite to Develop Open Source Framework
- ^ OpenHPC Wiki
- ^ Cluster Computing with OpenHPC
- ^ "Downloads – OpenHPC". openhpc.community.
External links
- OpenHPC: A Comprehensive System Software Stack
- Next Platform - OpenHPC Pedal Put To The Compute Metal
- HPCwire - OpenHPC Pushes to Prove its Openness and Value at SC16
- High Performance Computing: 32nd International Conference
- OpenHPC Slack channel
https://insidehpc.com/category/hpc-hardware/ http://www.openhpc.community/support/mail-lists https://github.com/openhpc/ohpc/wiki/Release-History-and-Roadmap https://www.slideshare.net/insideHPC/openhpc-project-overview-and-updates https://openhpc.community/support/faqwiki/ https://scholarworks.iu.edu/dspace/bitstream/handle/2022/21082/HPCSYSPROS16_Paper%204_Schulz%20et%20al.pdf?sequence=1 https://www.theubercloud.com/openhpc/
 | This Linux-related article is a stub. You can help Wikipedia by expanding it. |