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NVIDIA Jetson for Embedded, How high-performance and low-energy computing systems for deep learning and computer vision can help Robotics.

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Workshop on Multimodal Semantics for Robotic Systems (MuSRobS) IEEE/RSJ International Conference on Intelligent Robots and Systems 2015

NVIDIA JETSON FOR EMBEDDED

How high-performance and low-energy computing systems for deep learning and computer vision can help Robotics.

Serge Palaric

∗

Senior Director EMEA Embedded

NVIDIA

E-mail: N.A.

Short Bio

Serge Palaric joined NVIDIA in 2004 after 20 years working at different OEMs as Dell, Packard Bell and NEC on mobile devices at European level. Focused on system design wins at key global accounts; He is in charge of embedded business at NVIDIA covering Europe with a focus on IVA and Autonomous machines where Computer Vision and Deep Learning are key leading technologies.

NVIDIA Jetson TK1

Our NVIDIA Jetson TK11 development kit was the first mobile supercomputer to power next-gen embedded applications employing computer vision, as well as other on-board com- putationally intensive apps. It’s built around the revolutionary NVIDIA Tegra K1 SOC, a

∗To whom correspondence should be addressed

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Workshop on Multimodal Semantics for Robotic Systems (MuSRobS) IEEE/RSJ International Conference on Intelligent Robots and Systems 2015

4-Plus-1 quad-core mobile processor that combines the lowest power ARM Cortex-A15 CPU to highest-performance GPU that uses the same NVIDIA Kepler computing core designed into supercomputers around the world. Jetson TK1 enables industries to unleash the power of 192 CUDA cores to develop solutions in computer vision, robotics, UAV, IVA, and more, shaping the future of embedded.

References

(1) Jetson Embedded Hardware. https://developer.nvidia.com/embedded/develop/

hardware, 2015; [Online; accessed 20-October-2015].

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