NVIDIA Jetson is the world’s leading visual computing platform for GPU-accelerated parallel processing in the mobile embedded systems market. Its high-performance, low-energy computing for deep learning and computer vision makes Jetson the ideal solution for compute-intensive embedded projects like:
- Autonomous Robotic Systems
- Advanced Driver Assistance Systems (ADAS)
- Mobile Medical Imaging
Jetson TX1 is a supercomputer on a module that’s the size of a credit card. It features the new NVIDIA Maxwell™ architecture, 256 NVIDIA CUDA® cores, 64-bit CPUs, and unmatched power efficiency. Plus, it includes the latest technology for deep learning, computer vision, GPU computing, and graphics, making it ideal for embedded visual computing.
It’s built around the revolutionary NVIDIA Maxwell™ architecture with 256 CUDA cores delivering over 1 TeraFLOPs of performance. 64-bit CPUs, 4K video endcode and decode capabilities, and a camera interface capable of 1400 MPix/s make this the best system for embedded deep learning, computer vision, graphics, and GPU computing.
MIT students’ built self-driving mini-robot cars that can zip around a tunnel maze track while navigating its twists and turns. Students design and program algorithms using a Jetson TK1 embedded computer. Jetson TK1 helps the 1:10-scale cars deploy the open-source Robot Operating System, assess their environment and develop a language to help them race the fastest while careening around the course.
The course was so popular, its creator, Sertac Karaman, assistant professor of aeronautics and astronautics at MIT, is designing a bigger version for next year with Jetson at the core.
For next year’s course, Karaman has big plans — a Formula 1-style race arena with a dozen cars jostling for pole position. After harnessing the power of Jetson, he’s ready to add GPU-powered stereo cameras and feature detection.