GPU vs CPU Data Processing

19th March 2021 by Brytlyt

GPU-Accelerated Computing takes advantage of the power and performance of GPUs (Graphics Processing Units) instead of relying solely using CPUs (Central Processing Units). This accelerates process-intensive tasks across a variety of industries.

GPUs are specialised microprocessors 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.

This has led to a complete revolution in the way we think about processing data and has spawned an entire 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.

The modern processing technologies that Brytlyt offer, can give far greater data insights and level of performance than legacy systems have ever been able to offer.

What is GPU-Accelerated Analytics used for?

A tool is only as good as what it’s useful for; and the potential for GPU Data Processing is virtually limitless for process intensive operations across multiple industries. The vast computing power available from GPUs allows companies to extract useful & highly valuable business intelligence from large datasets, with incredible accuracy and speed. 

Brytlyt aims to generate smarter intelligence, quicker.

We understand the importance of data-driven business and can help you achieve it, so you’re able to find patterns and insight across huge amounts of data, in an instant.

How does GPU Data Processing work?

GPU Data Processing functions by assigning parts of an application to the GPU, as opposed to using traditional architecture, which uses CPUs that are much slower and requires significantly more hardware. CPU-based systems also rely on a level of manual processes by users and data scientists, like indexing and downsampling.

By contrast, GPU-based systems take in entire datasets, enabling users to instantly interactively visualise, query and power data workflows over billions of lines of data.

Uncovering value in large datasets is crucial – and legacy CPU systems can’t keep up

While a CPU handles all the core functions in a computer, a GPU acts as a specialised microprocessor with the ability to take over when intensive computations are required.

Why use Brytlyt GPU-Accelerated Analytics?

  • Brytlyt helps you interactively query, visualise, and power data science workflows over billions of records with a wide range of accelerated analytics solutions.
  • GPU service market review and expansion
  • Our end-to-end platform delivers decision support and business-critical insights.
  • Built on PostgreSQL, we empower users to analyse more data, faster and with ease.

Our unique GPU patent-pending IP technology has been developed to be at the very forefront of the transformational analytics revolution. Our next-generation platform with speed of thought analytics is built for ambitious businesses who want to harness their rapidly growing datasets of today and for tomorrow.

To learn more about how GPU acceleration can help give your team the competitive advantage, as well as learning more about the importance of data visualisation, read more here, or contact Brytlyt, market leaders in GPU accelerated analytics, for any queries you may have.