​Nvidia touts GPU processing as the future of big data

Nvidia plans to increase its presence in the commercial market, which it believes will need help in processing big data.

Nvidia is gearing up to tap into the big data business, in which Mark Patane, Nvidia ANZ country manager, has described will be a trillion dollar business over the next few years.

Speaking to ZDNet, Patane believes graphic processing units (GPU) will be a key solution to helping commercial businesses get through analysing their big data, and pointed out Nvidia has been working with the likes of Facebook and Google over the last two years to help them process their data.

"They came to us because they realise you can't use your normal every day computers because this data is just too much. We've been working with them for a couple of years using GPU," he said.

Dr Jon Barker, Nvidia machine learning solutions architect lead, further explained businesses are increasingly tasked with figuring out how to efficiently process all the data they are collecting, highlighting there are 2.5 exabytes of digital data produced daily, and that data is expected to double every three years.

"Most of that data is not tabular, structured data; most of it is imagery, audio, and text. It's obvious whether you're trying to measure the pulse of society, to understand the sentiment of your brand, you're trying to make trading decisions based on world events, or if you're trying to develop smart robots to assist surgeons, or self-driving cards, this data will be the fuel of your applications," he said.

"The question is how we triage that velocity of data to understand the content, and the answer to that is we need machines that can see, that can hear, that can read, and that can reason at superhuman levels and superhuman pace."

Patane believes the growth of big data will be an opportunity for Nvidia to widen its presence in the commercial market, beyond the current higher education and research field the company has long been providing GPU to.

"Whether you're Monash University, a big telco, Google, in health, a researcher -- it's got to be GPU," he said.

"The fundamental difference is that you can try and run data on non-GPU systems, but as soon as you hit the enter key and it starts doing algorithms that spinning wheel of death can take weeks before it comes back with an answer. With a GPU, you can do it a lot faster and the response will be in a matter of minutes."

However, using GPU to process big data is not new, according to Patane, who said it has long been used for engineering analysis, video analysis, and video playback for virus and DNA modelling.

Nvidia recently launched its DGX-1 server, powered by its Tesla P100 GPU, specifically to help businesses process big data, which Barker said will allow businesses to focus on application development, rather than data processing.