Why GPUs are taking over the enterprise

With IBM InterConnect just a few weeks away, we’re gearing up to showcase how the MapD graphics-processing-unit (GPU)-powered data analytics and visualization platform has evolved over the past year.
When MapD participated in InterConnect last year, we were just starting to ramp up. Our mission then, as now, remains unwavering: to provide the world’s fastest data exploration platform.
So much has changed. Since the last InterConnect, MapD launched its product offering and announced A round funding while steadily building on momentum throughout the year, culminating in the release of version 2.0 of the MapD Core database and Immerse visual analytics platform in December.
In the meantime, we were fortunate to pick up some prestigious awards including Gartner Cool Vendor, Fast Company Innovation by Design, The Business Intelligence Group’s Startup of the Year, CRN’s 10 Coolest Big Data Startups and Barclays Open Innovation Challenge.
One major reason for all this attention and praise is that GPUs are taking over the enterprise. We’ve written about this extensively in several blog posts, but GPUs are no longer a technology novelty item. They are mainstream, as Nvidia’s tripled data center revenues attest.
What makes MapD unique is that, from the ground up, we’ve built a querying engine and visual analytics platform that takes advantage of GPUs. With CPUs come the limitations of Moore’s Law. As more as more businesses place an emphasis on massive quantities of data, machine learning, mathematics, analytics and visualization, GPUs are poised to take over.
Here’s a simple example: say you want to run a query against a billion or more records, a pretty common request. With today’s legacy database solutions you should plan a two-martini lunch because that’s how long it’s going to take to run.
You better have your question nailed too, because if you want to modify it, you are going to want to eat dinner before you see the updated query again.
The experience is similar to the days of dial-up page load times, which wouldn’t that problematic if we didn’t know what real speed felt like.
In the past year, we’ve been able to validate our claims in a series of powerful independent benchmarks published by noted database authority Mark Litwintschick. To date, we remain the fastest platform (by a factor of 75) that he has ever tested against the 1.2 billion-row New York city taxi dataset.
We are delighted to be speaking at IBM InterConnect again. It is a homecoming in many ways. We can’t wait to show you how transformative the MapD platform can be when tackling big data problems.
Check out the session “Speed, Scale and Visualization: How GPUs are Remaking the Analytics Landscape in the Cloud,” at InterConnect Thursday, 23 March, from 11:30 AM to 12:15 PM.
Attend this session and more by registering for IBM InterConnect 2017.
We’re looking forward to another great event in Las Vegas. If you’d like to set-up an appointment or demo, send us an email at info@mapd.com.
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Quelle: Thoughts on Cloud