Cray is expanding its artificial intelligence products to make it easier to learn and start their own initiatives.
Clearly feeling that the influx of AI and deep learning are creating somewhat of a shortage of skills, and that people need a bit of help when it comes to adopting this technology, Cray’s using its supercomputing tech to help out.
The Accel AI Lab will be used to advance the development of deep learning technologies and workflows. It’ll also include NVIDIA Tesla V100 GPU accelerators, a new Cray Ulrika-XC analytics software suite, including TensorFlow, and an AI collaboration agreement with Intel.
The agreement with Intel will see Cray use the company’s AI tech to advance distributed deep learning and machine learning products.
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“Cray is committed to working closely with our customers, partners, and innovators in AI to drive the adoption of deep learning in science and enterprise,” said Fred Kohout, Cray’s senior vice president of products and chief marketing officer. “At Cray, we are bringing together a powerful set of innovative systems, software, deep learning architectures, and a hands-on lab environment to give organizations a trusted partner to advance AI workloads from pilot to production.”
In addition to the Accel AI Lab and all of its features, the supercomputing company is also introducing the first production-ready Arm based supercomputer with Cavium ThunderX2 processors and based on 64-bit Armv8-A architecture, to the Cray XC50 supercomputer.
“With the integration of Arm processors into our flagship Cray XC50 systems, we will offer our customers the world’s most flexible supercomputers,” said Fred Kohout, Cray’s senior vice president of products and chief marketing officer.
“Adding Arm processors complements our system’s ability to support a variety of host processors, and gives customers a unique, leadership-class supercomputer for compute, simulation, big data analytics, and deep learning. Our software engineers built the industry’s best Arm toolset to maximize customer value from the system, which is representative of the R&D work we do every day to build on our leadership position in supercomputing.”