Today NVIDIA introduced Jetson TX1, a small form-factor Linux system-on-module, destined for demanding embedded applications in visual computing. Designed for developers and makers everywhere, the miniature Jetson TX1 (figure 1) deploys teraflop-level supercomputing performance onboard platforms in the field. Backed by the Jetson TX1 Developer Kit, a premier developer community, and a software ecosystem including Jetpack, Linux For Tegra R23.1, CUDA Toolkit 7, cuDNN, and VisionWorks, Jetson enables machines everywhere with the proverbial brains required to achieve advanced levels of autonomy in today’s world.
Aimed at developers interested in computer vision and on-the-fly sensing, Jetson TX1’s credit-card footprint and low power consumption mean that it’s geared for deployment onboard embedded systems with constrained size, weight, and power (SWaP). Jetson TX1 exceeds the performance of Intel’s high-end Core i7-6700K Skylake in deep learning classification with Caffe, and while drawing only a fraction of the power, achieves more than ten times the perf-per-watt.
Jetson provides superior efficiency while maintaining a developer-friendly environment for agile prototyping and product development, removing extra legwork typically associated with deploying power-limited embedded systems. Jetson TX1’s small form-factor module enables developers everywhere to deploy Tegra into embedded applications ranging from autonomous navigation to deep learning-driven inference and analytics. Continue reading →
In the previous CUDACasts episode, we saw how to flash your Jetson TK1 to the latest release of Linux4Tegra, and install both the CUDA toolkit and OpenCV SDK. We’ll continue exploring the power efficiency the Jetson TK1 Kepler-based GPU brings to computer vision by porting a simple OpenCV sample to run on the GPU. We’ll explore computer vision further in a future CUDACast when we look at the VisionWorks toolkit from NVIDIA.
Today, cars are learning to see pedestrians and road hazards; robots are becoming higher functioning; complex medical diagnostic devices are becoming more portable; and unmanned aircraft are learning to navigate autonomously. As a result, the computational requirements for these devices are increasing exponentially, while their size, weight, and power limits continue to decrease. Aimed at these and other embedded parallel computing applications, last week at the 2014 GPU Technology Conference NVIDIA announced an awesome new developer platform called Jetson TK1.
Jetson TK1 is a tiny but full-featured computer designed for development of embedded and mobile applications. Jetson TK1 is exciting because it incorporates Tegra K1, the first mobile processor to feature a CUDA-capable GPU. Jetson TK1 brings the capabilities of Tegra K1 to developers in a compact, low-power platform that makes development as simple as developing on a PC.
Jetson TK1 is aimed at two groups of people. The first are OEMs, including robotics, avionics, and medical device companies, who would like to develop new products that use Tegra K1 SoCs, and need a development platform that makes it easy to write software for these products. Once these companies are ready to move to production, they can work with one of our board partners to design the exact board that they need for their product. The second group is the large number of independent developers, researchers, makers, and hobbyists who would like a platform that will enable them to create amazing technology such as robots, security devices, or anything that needs substantial parallel computing or computer vision in a small, flexible and low-power platform. For this group, Jetson TK1 offers the size and adaptability of Raspberry Pi or Arduino, with the computational capability of a desktop computer. We’re excited to see what developers create with Jetson TK1!
Tegra K1 is NVIDIA’s latest mobile processor. It features a Kepler GPU with 192 cores, Continue reading →