Attention enthusiasts, developers and creators. Are you working on a new embedded computing application?
Meet the Jetson TK1 Developer Kit. It’s the world’s first mobile supercomputer for embedded systems, putting unprecedented computing performance in a low-power, portable and fully programmable package.
Power, ports, and portability: the Jetson TK1 development kit.The Jetson TK1 development kit
It’s the ultimate platform for developing next-generation computer vision solutions for robotics, medical devices, and automotive applications.
And we’re giving away 50 of them as part of our Tegra K1 CUDA Vision Challenge.
In addition to the Tegra K1 processor, the Jetson TK1 DevKit is equipped with 2 GB of RAM, 16 GB of storage and a host of ports and connectivity options.
And, because it offers full support for CUDA, the most pervasive, easy-to-use parallel computing platform and programming model, it’s much easier to program than the FPGA, custom ASIC and DSP processors that are typically used in today’s embedded systems.
Jetson TK1 is based on the Kepler computing architecture, the same technology powering today’s supercomputers, professional workstations and high-end gaming rigs. It has 192 CUDA cores, delivering over 300 GFLOPs of performance, and also provides full support for OpenGL 4.4, and CUDA 6.0, as well as the GPU-accelerated OpenCV.
Our Tegra K1 system-on-a-chip offers unprecedented power and portability.Our Tegra K1 system-on-a-chip offers unprecedented power and portability.
Entering the Tegra K1 CUDA Vision Challenge is easy. Just tell us about your embedded application idea. All proposals must be submitted April 30, 2014. Entries will be judged for innovation, impact on research or industry, public availability, and quality of work.
By the end of May, the top 50 submissions will be awarded one of the first Jetson TK1 DevKits to roll off the production line, as well as access to technical support documents and assets.
The five most noteworthy Jetson TK1 breakthroughs may get a chance to share their work at the NVIDIA GPU Technology Conference in 2015.