Every March the South by Southwest (SXSW) music, film and interactive festivals and conferences draw tens of thousands of artists, fans and techies to Austin, Texas.
This year Cray was asked to join the Raptor House 2-day invitation-only music, culture and technology event, which has previously been attended by such varied guests as Deepak Chopra, Kanye West and Willie Nelson. I participated in a panel on the Internet of Things (IoT) — the network of “connected” devices such as smart cars, thermostats, electricity meters and wearables — and discussed some significant opportunities for using the large volumes of data generated by these devices. IDC estimates that by 2020 there will be 20 billion such devices on the Internet.
While the benefits of smart cars, smart cities, smart watches and so on are widely discussed, one interesting but lesser-known use case is predictive maintenance. The ability to predict when a component will fail is a tremendous benefit. Imagine being informed proactively that a critical part of your car is at risk of failure — before it leaves you stranded on a busy highway. Studies indicate that predictive analytics could prevent over 70% of breakdowns and reduce maintenance costs by up to 30%.
On the other hand, the rise of the IoT can also lead to new threats. Last year a group of 100,000 devices unwittingly participated in a global cyber-attack that sent over 750,000 spam and phishing emails. Many of these devices were smart TVs, home media centers and routers that were exploited by taking advantage of loopholes like unchanged default admin passwords. Imagine what it could mean to have a compromised refrigerator, home thermostat or electricity meter.
To effectively deliver the benefits of the IoT and also address its risks, we need a new approach to rapidly ingest, analyze and store the vast quantities of data it generates. That requires the convergence of high performance computing and big and fast data analytics. Cray is at the forefront of this convergence, and during the panel I shared our experiences applying Cray’s technology to related use cases. My co-panelists discussed issues such the infrastructure and backbone requirements for transporting data, and how best to make use of our scarce wireless spectrum with so many connected devices.
One of my SXSW highlights was the number of people I encountered who had used Cray supercomputers to solve big computational challenges like climate modeling, nuclear stockpile remediation and genomics — and the other highlight was the festival’s great live music!
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