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GPU based industrial computing



GPU-based industrial computing


Anyone who works with IT has a lot to do with GPUs everyday. Whether they are being used to render the computer graphics needed for office workers, or they are being built into a computer at an IT manufacturer such as TX-Team, the applications of GPUs in business are seemingly endless. However, what about the use of GPUs in manufacturing plants that may appear to be less connected to the topic of computers? Are they still as useful?
The short answer: yes, but in what ways? Well, to understand this, it may be useful to look at the basic function of a GPU.


What is a GPU?
A GPU is a computer processor that uses accelerated calculations to render high-resolution images and videos. It is comparable to a CPU in that they have similar components, such as cores and memory, and they function in a similar way, computing tasks or calculations quickly and effectively. However there is one crucial difference. While CPUs process tasks sequentially, GPUs use something called “parallel processing” to divide big tasks into smaller sub-tasks that are distributed to each processing core and thus executed simultaneously. Due to the advancement of GPUs over the years, they are now capable of way more than just graphic processing. Their high level of processing power makes GPUs especially useful for specialized tasks such as machine learning, data analytics and other applications in artificial intelligence. And that’s where they come into play in the manufacturing industry.



GPUs in manufacturing – Machine learning
Machine learning is a type of AI which describes the process of feeding computers with lots of data, or data sets, allowing them to learn from this data automatically and improve processes on their own. Machine learning has many applications in the world of manufacturing.

Automation:
One of the most common uses of machine learning, and thus GPUs, is the enhancement of quality control. Often this has to be done by human inspectors who examine each product for defects. With the introduction of machine learning however, it is possible to train computers to detect faults automatically by learning from images or other data sets. Machine learning can also be used to automate the actual manufacturing process. Robots equipped with these capabilities can learn to perform various jobs, such as welding or assembly. This would improve production, accuracy and efficiency.

Production:
Machine learning gives manufacturers the ability to easily create and customize products based on the customer’s demands. This allows business to quickly supply customers with in-demand products that fit their needs without incurring significant additional costs for the business.


The future of machine learning and GPUs
There are many more ways GPUs can be used in the manufacturing industry as well as in other business sectors. In the coming years, we will no doubt see an increase in the implementation of this technology in different avenues of life, in and out of the workplace.
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