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Maximising High Performance Computing for Big Data Processing

[fa icon="calendar"] 28/03/18 08:12 by Editorial Team

Editorial Team

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There are many governments, education, mining, betting, pharmaceutical, weather and science companies that require High-Performance Computing (HPC)for Big data processing.

Companies with huge amounts of data to manage and process find HPC very useful. HPC is mostly used, to solve big scientific and engineering issues. So, how can companies maximise HPC, in processing company data?

What is high performance computing?

High-performance Computing is the practice of synthesising computer power, in a way that offers much higher performance than what a normal workstation or desktop computer could. No wonder High-Performance Computing is so popular in engineering, science and business sectors. You have also heard of people using HPC in mining cryptocurrencies.


HPC machines are more intricate than typical desktop computers. In High-Performance Computing, where the side of data files is high, data storage is centralised. The big volumes of data files also require more expensive networking communications. For these reasons, small companies are advised to avoid HPC and use Hadoop instead. Although HPC is quite effective, Handoops are easier to run and are less expensive.

 

Factors to consider before moving to HPC

Before moving to HPC, companies should understand why they need the technology and how it will be used to improve business. HPC involves installation of very expensive hardware, and thus should only be used in large companies.

 

Support

Note that management does not have to be experts at High-Performance Computing. However, management needs to hire high-level support, before making any software and hardware investments into HPC. Support should be able to distinguish HPC from old analytics and understand how to apply HPC to meet business objectives.

If you are going to run an in-house operation, you should train and position your team to be proficient with HPC. If its the first time the company is using Higher Performance Computing, try hiring consultants to start the HPC apps and train the rest of the staff. 

Setting up and long-term operation of HPC will be more effective under the supervision of data scientist. Data scientists also assist in developing complex algorithms for the HPC. The company will also require brilliant system programmers, versed in Fortran or C+ skills and able to work in parallel processing environments.

 

Hardware

When it comes to buying HPC, the preconfigured hardware is the best. After purchase, companies can customise the hardware to their specific needs. It is important to weigh the financial risk involved in buying an HPC. 

 

Cost and return on investment

Yes, High-Performance Computing is the 'magic wand' that organises and processes big data. -But it is unnecessary if the company does not have outstandingly huge traffics of data to process. Make sure that the HPC is cost-justifiable for the company and that its return on investments is (ROI) is impressive enough for the management or board. 



In conclusion, Higher Performance Computing is very utilitarian in processing big data. Please note that cloud HPC is good for companies which run only twice or thrice a week. However, bigger companies require an in-house operation for accurate and speedy processing of data.

Categories: Big Data

Editorial Team

Written by Editorial Team

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