What is Jetson and What is it Used For?

What is Jetson？

Jetson is a series of embedded hardware platforms developed by NVIDIA, specifically tailored forartificial intelligence (AI) applications and edge computing. This platform integrates advanced graphics processing units (GPU), central processing units (CPU), memory, and various other hardware components designed to meet the demands of embedded systems that require high-performance computing. Such applications include robotics, autonomous vehicles, smart city technologies, and the industrial Internet of Things (IoT).

Key Features of Jetson

1. High Performance:

• The Jetson platform is built on NVIDIA’s GPU architecture, which includes generations such as Maxwell, Pascal, Volta, and Ampere. This infrastructure provides robust parallel computing capabilities, facilitating advanced computational tasks.
• This solution is appropriate forartificial intelligence inference, deep learning applications, computer vision, and various other tasks that require significant computational resources.

2. Low Power Design:

• The system is optimized for embedded devices, exhibiting power consumption typically ranging from 5W to 50W. This characteristic renders it particularly suitable for mobile applications, including robotics and drone technology.

3. Complete Ecosystem:

• The Jetson series is compatible with the NVIDIA JetPack SDK, which encompasses a comprehensive suite of development tools and libraries designed for deep learning inference (TensorRT), computer vision (VisionWorks), and CUDA programming.
• The system provides an extensive array of hardware interfaces, including USB, PCIe, and GPIO, which facilitates seamless connections with various sensors, cameras, and additional peripheral devices.

4. Flexibility and Scalability:

• Jetson modules are available in a range of series, including Nano, Xavier, and Orin, to address a variety of requirements, spanning from entry-level applications to advanced high-performance edge computing solutions.

What is Jetson used for?

Jetson is predominantly utilized for applications involving artificial intelligence (AI) and edge computing that necessitate high-performance processing within compact, energy-efficient devices. It is extensively embraced across the following domains:

1. Robotics:

• Facilitates autonomous navigation, object detection, and real-time decision-making capabilities for industrial, service, and agricultural robotics applications.

2. Autonomous Vehicles:

• The technology facilitates real-time image processing, environmental sensing, and obstacle avoidance for unmanned aerial vehicles, autonomous ground vehicles, and self-driving cars.

3. Smart Cities:

• Facilitates advanced intelligent surveillance, traffic management systems, and urban infrastructure monitoring to develop more efficient solutions for smart cities.

4. Industrial IoT (Internet of Things):

• This technology enables predictive maintenance, facilitates real-time analytics, and supports automation within industrial environments.

5. Healthcare:

• Utilized in AI-enhanced medical imaging, diagnostics, and various healthcare applications.

6. Education and Research:

• This platform provides an environment for students, researchers, and developers to investigate and develop projects in the fields of artificial intelligence and embedded systems.

How many series does Jetson have?

The Jetson family currently consists of seven main product families, which are categorized by performance and application scenarios as follows:

FAQs

What is Jetson Nano good for?

The Jetson Nano is an exemplary platform designed for educational purposes, as well as for the development of artificial intelligence applications. It is particularly well suited for lightweight edge AI projects, including object detection, speech recognition, and fundamental robotics. With its low power consumption, ranging from 5 to 10 watts, and its cost-effectiveness, the Jetson Nano is an ideal choice for students, hobbyists, and developerswho seek to explore artificial intelligence, computer vision, and deep learning within a compact and energy-efficient framework.

Is the NVIDIA Jetson a GPU?

No, the NVIDIA Jetson represents a series of embedded hardware platforms that encompass not only a GPU but also a CPU, memory, storage, and various interfaces. The GPU serves as a critical component within the Jetson platforms, leveraging NVIDIA’s advanced architectural designs, such as Maxwell, Pascal, Volta, and Ampere. These technologies offer robust parallel computing capabilities, specifically tailored for artificial intelligence applications.

Is the NVIDIA Jetson an FPGA?

No, the NVIDIA Jetson platform is distinct from a Field-Programmable Gate Array (FPGA). An FPGA is ahardware device that can be reconfigured to execute specific tasks through the arrangement of its logic gates. In contrast, Jetson platforms utilize fixed hardware architectures, such as Graphics Processing Units (GPUs), which are optimized for parallel computing and deep learning applications. While FPGAs offer a high degree of customization for particular tasks, Jetson provides a comprehensive, high-performance solution specifically designed for artificial intelligence, robotics, and computer vision applications.

What programming language does NVIDIA Jetson use?

NVIDIA Jetson supports multiple programming languages, making it versatile for different AI, machine learning, and robotics applications. The primary languages commonly used with Jetson include:

1. Python: Widely used for AI, machine learning, and deep learning tasks due to its simplicity and powerful libraries like TensorFlow, PyTorch, OpenCV, and others. Python is highly popular for developing AI models and computer vision applications on Jetson.
2. C++: Often used for performance-critical applications, especially in robotics and computer vision. C++ can be used to access lower-level hardware interfaces and optimize code for real-time performance.
3. CUDA (C/C++): Jetson platforms leverage NVIDIA’s CUDA toolkit, which allows you to write programs that can run on the GPU. CUDA is essential for parallel computing tasks, deep learning, and AI inference. It’s mostly used with C++ but can also be integrated with Python using libraries like CuPy or PyCUDA.
4. JavaScript: For web-based applications, JavaScript can be used with Node.js or frameworks like TensorFlow.js to run AI models in a browser or on a server, which can be used in edge applications.
5. Other Languages: Jetson supports a variety of other languages through APIs and frameworks. For example:

• Java: For some IoT applications.
• MATLAB: For scientific and engineering applications, often for prototyping AI models.

Jetson’s software ecosystem, especially with the NVIDIA JetPack SDK, offers a variety of tools and libraries in these languages to facilitate development for AI, robotics, and IoT applications.