THE BRIGHT BLOG

You've probably noticed an uptick in talk about machine learning and deep learning in your circle of HPC friends and colleagues. People are finding new ways to apply deep learning to all sorts of business problems and using HPC clusters to provide the compute power. But things are changing so rapidly that it's hard to keep up with all the new libraries, frameworks, architectures, and tools you can choose from. 

CHPC has been a Bright customer since 2015. We first wrote about CHPC shortly after the South Africa-based research organization had chosen Bright Cluster Manager to manage the infrastructure of its supercomputer facility, and since that time, our two companies have built a strong and dynamic relationship.

With Deep Learning experiencing unprecedented momentum in the HPC market, I find it exciting that Bright’s development team is focusing in on this area, and is involved in cutting edge Deep Learning innovation.

Rich Brueckner Gets an Update from Bright Computing Computing CEO Bill Wagner.

Whether you’re just dabbling with deep learning or deeply mired machine learning, you know how rapidly things are changing. New tools, new techniques, new algorithms and methods…it’s hard to keep up.

Need help? I have a suggestion you may like. The new Dell EMC Machine Learning Knowledge Center.

Yesterday, I sat in on an interesting session about the HPC market by Intersect360. The talk was led by Addison Snell and Christopher Willard and started with an informal discussion about what the audience would like to see in Addison’s Analyst Cross Fire panel taking place Wednesday, June 21 at 2:45 in the Panorama Room.  People want to know how HPC can support real-time data analytics for vertical applications at the Edge, Deep Learning and AI, and what the future looks like for these markets.

These days business owners and managers are quite familiar with “the cloud.” But many don't realize that the cloud actually comes in two distinct flavors.

What most people have in mind when they speak of the cloud is offerings like Amazon Web Services (AWS) or Microsoft Azure, which are set up to host the data and applications of any customer who desires to use that platform. Because they are available to be shared among all comers, and are accessible through the public internet, such services are called the “public cloud.”

Remember the feeling you had when you first learned to drive a car? Everything was new to you. Sure, you knew what a steering wheel was, and what each pedal was for, but you had to learn how much steering input you could safely use at different speeds. Discovering just how much clutch and throttle was needed to get rolling without stalling doesn’t come easily to most people. And I’ll bet figuring out how hard (and how soon) to press the brake pedal as you came up behind another car at a stoplight created a few anxious moments for you and your instructor. But what does this have to do with managing clusters? In many ways, learning how to drive a cluster is much like learning to drive a car. At first, it can seem overwhelming, but once you master the individual skills, you can use them together to create a genuinely exciting experience.

We just got back from the GPU Technology Conference in Silicon Valley, where it was hard to miss the focus on AI applications and deep learning. And that makes sense, given the significant role GPUs are playing in the recent rise in practical applications of deep learning.

Bright Computing will be exhibiting at the GPU Technology Conference (GTC 2017) being held May 9-11 at the San Jose Convention Center, and we expect it to be an exciting event!