Critical Role of HPC Storage in Autonomous Vehicle Development

Self-driving cars were once only the stuff of science fiction. But thanks to recent computing advances, they are becoming more of a reality every day. Still, a number of issues need addressing before fully autonomous vehicles share our roadways. And one of the largest is capturing and processing the data generated by fleets of training cars. This massive amount of data creates an unprecedented storage challenge that autonomous vehicle development companies cannot overcome using their existing enterprise storage architectures. Luckily, here at Cray we’ve made it our mission to provide technology that solves the world’s most complex computing challenges, so this problem is right in our wheelhouse. First, a little background. Driving a ... [ Read More ]

Autonomous Vehicle Development Drives Extreme Storage Requirements

We can probably all agree that driving a car today is a radically different experience than it was just a few years ago. The next generation of vehicles – self-driving cars – are poised to take modern automotive features a quantum leap forward and provide totally different ways to get from point A to point B. One of the reasons fully autonomous vehicles are still a few years off is that designing an AI model that can safely and accurately drive a car is turning out to be an incredibly complicated task. The two main challenges are simulating every possible driving scenario that could occur so the model can be trained to identify the appropriate reaction, and handling the vast volume and variety of data generated by fleets of training ... [ Read More ]

Boost Your HPC & AI Knowledge with Fall Learning Series Webinars

Summer is almost over and fall is the perfect time to refocus, reengage, and reinvest in learning how to overcome some of your biggest HPC challenges. To help get you on track, Cray is offering a September Learning Series of webinars designed to address four of the most frequently asked questions we get in areas ranging from artificial intelligence to storage and compute to software. Join us for any — or all — of the sessions to learn, ask questions and engage with industry thought leaders. Tuesday, 9/11, 9 a.m. PT: The Three Steps: Focusing on Workflow for Successful AI Projects As artificial intelligence (AI) has gained mainstream acceptance, there's been a lot of focus on the systems used to develop and train models. But ... [ Read More ]

How to Choose the Right Data Storage the First Time

It used to be that only two factors drove an organization’s choice of data storage platform: performance and cost. But along came data… and then more data and bigger data and, well, it’s not stopping. Yep, data got big and traditional approaches to storage selection and management don’t work anymore. From where we sit as a designer of complete high-performance computing and storage systems, we’re seeing commercial and research institutes scrambling to keep up with data growth. We’re seeing some large research institutes planning infrastructure for storage solutions up to 250 petabytes in size. On the commercial side, we’re seeing AI research and development generating data of even larger magnitude. Data growth is flipping company ... [ Read More ]

Business Cards Change, but the Passion for Open-Source Lustre Doesn’t

DDN announced today that the Intel Lustre® team has found a new home at DDN. In an open-source, community-owned model it doesn’t really matter which logo is on the business cards of the developers who are contributing to the community. That's a good thing, because there have been a lot of changes for two of the key contributing development teams in this decade. Driven by a vibrant and passionate community, Lustre® has quickly become the de facto standard in leadership-class supercomputing environments around the world, and now 77% of the Top 100 systems are using Lustre (June 2018 top500.org list). It’s easy to see why when you compare open-source Lustre’s benefits to other expensive, proprietary file systems. Cray ... [ Read More ]