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How powerful is the Jetson TX2?
Jetson TX2 is the fastest, most power-efficient embedded AI computing device. This 7.5-watt supercomputer on a module brings true AI computing at the edge. It’s built around an NVIDIA Pascal™-family GPU and loaded with 8GB of memory and 59.7GB/s of memory bandwidth.
Is Jetson Nano an embedded system?
Nvidia Jetson is a series of embedded computing boards from Nvidia. The Jetson TK1, TX1 and TX2 models all carry a Tegra processor (or SoC) from Nvidia that integrates an ARM architecture central processing unit (CPU). Jetson is a low-power system and is designed for accelerating machine learning applications.
What is the Nvidia Jetson used for?
NVIDIA® Jetson Nano™ Developer Kit is a small, powerful computer that lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. All in an easy-to-use platform that runs in as little as 5 watts.
What is Nvidia Jetson TX1?
NVIDIA Jetson TX1 is an embedded system-on-module (SoM) with quad-core ARM Cortex-A57, 4GB LPDDR4 and integrated 256-core Maxwell GPU. Useful for deploying computer vision and deep learning, Jetson TX1 runs Linux and provides 1TFLOPS of FP16 compute performance in 10 watts of power.
Does Jetson TX2 have WIFI?
The WIFI antenna connection can be found on the side of the Jetson TX2/TX1 module.
Is the Jetson Nano worth it?
Even if used as a standard SBC – the Nano is a great deal (the Shield is even better a deal for that though imo) compared to many other boards that cost the same or more. The benefit with the Nano is the access to the Jetson Package and a platform to learn and test the Cuda software.
What architecture is Jetson TX2?
Jetson TX2 accelerates cutting-edge deep neural network (DNN) architectures using the NVIDIA cuDNN and TensorRT libraries, with support for Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTMs), and online reinforcement learning.
How do you use Jetson TX2?
Configuring the Jetson TX2
- Take the USB Micro-B to USB A cable included in the developer kit and connect your Jetson TX2 to the Linux Computer.
- Connect a Monitor, Keyboard and Mouse.
- Take the AC adapter included in the developer kit and connect your TX2 to an outlet.
What is Jetson TX2 kit?
The Jetson TX2 Developer Kit gives you a fast, easy way to develop hardware and software for the Jetson TX2 AI supercomputer on a module. It exposes the hardware capabilities and interfaces of the developer board, comes with design guides and other documentation, and is pre-flashed with a Linux development environment.
Does Jetson Nano support Cuda?
The Jetson nano can be used as a general purpose Linux-powered computer, which has advanced uses in machine learning inference and image processing, thanks to its GPU accelerated processor. Nvidia calls this special framework that enables parallel computing on the GPU the CUDA (Compute Unified Device Architecture).
What are NVidia Jetson™ TX2 modules?
NVIDIA ® Jetson ™ TX2 series modules give you exceptional speed and power-efficiency in an embedded AI computing device. Each supercomputer-on-a-module brings true AI computing to the edge with an NVIDIA Pascal™ GPU, up to 8 GB of memory and 59.7 GB/s of memory bandwidth, and a wide range of standard hardware interfaces.
Can I use Denver cores on the Jetson TX2?
Regarding question #2, all of Concurrent’s testing on the Jetson TX2 has indicated that any use of the Denver cores can negatively impact the entire system’s real-time performance. Regarding question #3, Concurrent has tuned RedHawk on the TX2 to ensure optimum real-time performance.
What is the TX2 supercomputer?
Jetson TX2 is a 7.5-watt supercomputer on a module that brings true AI computing at the edge. It’s built around an NVIDIA Pascal ™ -family GPU and loaded with 8 GB of memory and 59.7 GB/s of memory bandwidth. It features a variety of standard hardware interfaces that make it easy to integrate into a wide range of products and form factors.
Does the Jetson TX2 have a negative impact on determinism?
Regarding question #1, Concurrent has spent considerable time testing the Jetson TX2 and we’ve seen that using the Denver cores can always negatively impact determinism, even on fully real-time shielded non-Denver cores.