By: Hetal Pachchigar
We can’t argue on that fact that, the technology machine learning (ML) is evolves rapidly. Recently, SC19 super-computing conference discussed that highest-performance computing (HPC) is the solution of this world. This technology is solving most challenging problems. Nowadays, developing system is based on machine learning.
Machine learning is essential tool in many fields like: medical diagnoses, designing of intelligent system etc. There also alternative methods of AI to solve different problems like: resource utilization, predicting of running time, optimization of load balancing, job scheduling, process migration.
This works aims to analyse the convergent of HPC and AI, and it comes out in two different ways: it helps to reducing time in machine learning via HPC system, and also it helps to data processing in big data analytics and handling problems appeared on the development of the distributed computing systems.
Big data analytics using machine learning (ML).
How ML and big data analytics are connected? ML is a set of algorithms that can learn from data. Big data is a type of data that can be supplied into analytics system so that ML module can learn.
A good way to think about the relationship between Big data and Machine Learning is that the data is the raw material that feeds the machine learning process. Machine learning and Big data analytics are not a symmetrical relationship. You need machine learning for analytics big data but you don’t need big data to able to use machine learning.
There are four V’s in big data
1. Volume- Amount of data.
2. Velocity- Speed of processing data.
3. Variety- kind of data which has been collected and processing.
4. Veracity- quality of data.
Usually, machine learning algorithms are used to label the incoming data and recognize patterns in it, that can translated into valuable insights that can be further implemented into business.
Best example of ML and Big data is Spotify, it is using a very efficient system that analyses the user’s listening history, search queries, listening stats, and other expressed behavior to construct personalized playlists.
Usage HPC in business.
HPC are used by government agencies, research institute and the largest corporations. The ability of High performance computer is to process large data sets and perform complex calculation at high-speed. On machines that cost hundreds of millions of dollars -- was not a critical business need for many enterprises. HPC also provides best security and enough space for storing large number of information.
Industry data shows HPC's growing appeal. According to Hyperion Research, the high-performance computing market for businesses will grow at annual growth rate of 9.8% from 2017 to 2022. "Prices start at well under $50,000 today. That's affordable for many types of organizations," said Steve Conway, senior research vice president at Hyperion Research.
For IT and business leaders, it's time to get up to speed on HPC. They must enable their organizations to grab hold of transformative insights, while avoiding foolish forays into unexplored territory with uncertain returns.
There are many more things which can be done by AI and HPC. HPC and AI is changing the world. Thus technology is making our life easy. It will be very useful for load-balancing, in learning system etc. Hopefully, this technology brings best only and not worst for the world.
Comments