Everything an organisation should know about Cloud-Based GPUs

We’re truly living in an exciting time, in terms of the rapid advances being made in Cloud-Based GPUs. Cloud-based business analytics software makes a good business case for itself as an increasingly appealing proposition for enterprises of all sizes.

With the ability to scale with the growth of an organisation, as well as how current demand dictates; the notion of having infrastructure and functionality on tap without the traditional down payment of investment makes a lot of sense, however you look at it.

The way a GPU handles data is very different to that of a CPU. As a specialised microprocessor, GPUs are composed of hundreds of cores that can handle thousands of threads simultaneously. This means GPUs are particularly well suited for doing specific tasks incredibly well – making them perfect for taking on repetitive and specialised computing tasks at speed.

What are cloud-based GPUs used for?

Cloud-based GPUs have completely reshaped company IT architecture over the past few years, due to their ability to automatically scale computing resources, based on requirements. Over the next few years, the vast majority of organisations around the globe are expected to have systems that use cloud-based GPUs to meet at least some level of their computational needs.

As the cost structure for cloud-based systems works like a utility (in which there’s no upfront cost for the infrastructure) paired with the ability to scale with the growth of an organisation, this elasticity is an undeniable benefit for all manner of businesses. 

Process-intensive tasks that can be accelerated by cloud-based GPUs benefit a variety of industries, including (but not limited to) insurance, financial, oil & gas, telecoms, DNA & genomics, pharmaceuticals, defence, logistics and many more…

The cloud-based GPU industry is set to grow exponentially over the coming years, as the applications for GPUs widen every day. As a specialised microprocessor, GPUs have the ability to take intensive computations and entire datasets on board, enabling users to instantly and interactively visualise, query and power data workflows over billions of lines of data.

The colossal computing power available from cloud-based GPUs can extract and process business intelligence from huge datasets with incredible speed and accuracy.

Predictive analytics is a part of business intelligence that’s becoming increasingly augmented by both Artificial Intelligence and Machine Learning, using statistics and modelling to determine future performance and conclude potential outcomes, based on both historical and current data. 

AI and ML can power predictive analytics to better identify patterns in data that can determine the likelihood of future emergence. This allows organisations to decide where best to focus resources, thus, be able to make intelligent predictions about the future.

This has led to a complete revolution in the way we think about processing data and has spawned an entirely new industry of companies taking advantage of the continued advancements in GPU hardware. Businesses around the world are unlocking their analytics potential by updating their technology to take advantage of the vast amount of data available.

By using Brytlyt’s GPU acceleration, businesses can leverage not just vast datasets of billions of rows of data, but can also use the very latest data available through speed of aggregation and processing. Historically, users would have to devote time (typically overnight) towards aggregating datasets – putting them at a disadvantage with a lack of access to the very latest information. With Brytlyt’s GPU technology, users can harness their complete datasets with greater flexibility and agility as well, processing in milliseconds.

The use of cloud-based GPUs is growing exponentially in a variety of fields of research and commercial ‘big data’ applications, including Business Analytics, Location Intelligence, Data Science & GPU Analytics, Visualisation, Deep Learning & Machine Learning.

In the future, cloud-based GPUs will play their part in keeping planes in the air, assisting researchers in curing disease, helping to mitigate the impacts of natural disasters, and also making sure your autonomous car can drive you safely to work.

Moore’s law has correctly suggested for over five decades that we can expect the speed and capability of computing to increase every couple of years with costs reducing proportionately.

While GPUs have benefited from Moore’s law in the same way as CPUs, they’re not constrained in the same way. As GPUs have the ability to ‘spread’ across larger pieces of silicon, in very basic terms, a more powerful GPU can be achieved when the number of GPU cores are increased. This accounts for the monumental rate of progress being found in the GPU industry, and why progress isn’t looking to slow down at any point soon.