Technology has had a history of numerous products that were developed for one task and later they were tweaked or merged with one or more technologies for providing a better solution to a whole different problem.
We are going to talk about a similar case here that has brought a revolution in the IT industry.
The merger of High-Performance Computing and Artificial Intelligence can be a good thing for the computer industry as the systems can become cheaper.
Just imagine this – the common hardware base which is the computer, network and storage when deployed for modern high-performance computing and AI systems, will bring down the research and development costs.
The research and development will occur on a single system instead of two different systems. However, this is just one of the benefits that the merger of AI and high-performance computing can bring. The benefits are plenty and it becomes essential to know the reasons that triggered the HPC and AI convergence at the first place.
Technology has a history of expiring ideas which are not being able to cope up with the market. We have also been the witness to various technologies diminishing as and when something superior launched and seized the market. There is no turning back once users adapt to a new technology better and faster than the older one. However, with HPC and AI, this is certainly not the case. Since their inventions, they have only become more and more powerful and well-equipped.
The discovery of hyper-converged infrastructure not only allowed users like major companies to consolidate their compute, networking, and storage at one place but also equip them with the most powerful technology to manage operations at a single platform. Accepting the fact that HPC users have gathered all the knowledge and abilities to converting a workload to a large base of customers is the best option to go with right now. What must also be accepted is that Artificial Intelligence still has a long way to go and it is still in its early stages with innovation knocking on the door.
Have you wondered what’s the use of these supercomputers? Well, there are many companies with huge workloads that have to manage data in plenty each second. Identical data has to be run millions of times to process the information and this is where supercomputers come into use. The value of HPC systems is immense which is sufficient to justify the need for the speed of supercomputers.
The data being generated at workplaces is so huge at times that many high-performance computing users even claim that it is the huge data that people in the early 90s were talking about. With the increase in the amount of data, the efficiency of supercomputers is also increasing.
AI comes into the picture when the enormous data being produced is to be transformed into an easily understood format. AI could do this job with ease on its own separate system built for that specific purpose. What’s hectic is the time and resources required to move the huge amount of data from the infrastructure where the data is being produced to the AI system. Hence, a system where the HPC and AI can be merged to save a considerable amount of time, data and resources is the practical option to go with for your company.
What does a workplace require in the 21st century? Models that are huge enough to handle all the data and speed that is fast enough to read all the data being produced.
AI has enabled workspaces across the world to analyze simulation data with speed and efficiency, no doubt! Apart from this, it has also given users an option that can easily replace the expensive computational parts in a workspace.
As an example, let’s consider this. Scientists have finally been able to land themselves on a method that can efficiently replace the old system they used to study collision data. Scientists have replaced the Monte Carlo methods with generative adversarial networks (GANs). Now they have a system which can give them more accurate results while measuring particle energy.
The AI code has successfully replaced the old system by producing similar results at a faster pace.
Enterprises are finding it hard to manage huge data and are taking resort to install numerous systems that can efficiently administer the same. Scientists have been busy in determining various data analytics techniques to help enterprises. And sadly the techniques they came up with is not proficient at times as they are totally reliant on human data-interpreting.
Human judgement is still irreplaceable but AI can help humans with working on recurring data that require a lot of calculation. Imagine your employees mishandling all the data that is flowing in your company’s servers ignoring other tasks on hand. The environment won’t only become complex, but the overall productivity will also decrease.
The Internet of Things (IoT) is making its mark in the market and the influx of data is only going to increase. With all such predictions, it becomes extremely essential for enterprises to adopt AI-enabled technology and an environment where AI and high-performance computing can work together saving the time, costs, space and also increasing the overall productivity.
The history of technology has seen a change in the way data centres were created and managed after the advent of virtualization. The same applies to various IT managers as slowly and gradually, most of them are making a shift to architectures that are capable of handling complex plethora of data. If you are still lingering on with the custom architectures that have a narrow range of workload, then your enterprise might be in grave danger to get sidetracked by your competitor who has already made the move.
This must not be hard to believe after numerous companies have adopted hyper-converged infrastructure (HCI) to get a more flexible architecture where they can easily manage their tasks of compute, networking, and storage all at the same place.
HPC and AI, when merged together for an enterprise, data preparation and handling can be done on a single platform easily and effectively. IT managers realize the need for a merged system.
We know that both high-performance computing and AI have much to offer to the world and both of these are marvellous in their work and capabilities. The potentials that AI and HPC carry with each other can be the best compliment and provide unique and unparalleled support to each other.
After you have reached this far, it is natural for you to ask about the benefits that favour the merger of HPC and AI prediction. As an industry expert, for long we won’t end this blog without answering this critical question.
Deep Learning or DL is the faster-growing field in AI as compared to Machine Learning or ML. The success of AI can largely be credited to its efficiency in analyzing enormous data in a short period. AI can solve a wide range of problems for various industries. The merger is only going to make the process more efficient in analyzing and managing the computing all at the same place at a high speed.
The innovations will be unstoppable and so will the data that is being produced. The merger will increase the possibility and the range of discoveries to put a faster and better solution in customer’s hands.
Data is the king and the enterprise that will be more efficient and fast in dealing with the enormous data that is about to come in will be the big player in the market. The merger of high-performance computing and artificial intelligence promises a massive gain in performance as compared to the traditional system with separate architecture for both.
GBB is an end-to-end IT Infrastructure Solutions and Services Company based in Hyderabad. We focus on helping customers transform their businesses through the innovative use of technology. We have the aim of providing our clients with excellent service by partnering with the best vendors in the respective areas.