Exploring the Distinctions: NVIDIA Jetson vs. Traditional IPC

Why should you choose NVIDIA Jetson-powered computer over a traditional Industrial PC

In today's rapidly evolving technological landscape, one question consistently arises among our customers and partners: “What sets NVIDIA Jetson apart from traditional PCs, and why should we choose it?” This question goes beyond simple curiosity; it touches on the core of strategic decision-making for businesses looking to harness the power of AI and edge computing. To provide a comprehensive answer, we talked to Felipe Leiva, our Technical Project Manager. Read on to discover why NVIDIA Jetson stands out as the preferred choice for cutting-edge AI applications.

NVIDIA Jetson: what is it and its primary functions

First, let’s define what NVIDIA Jetson is and its primary functions. NVIDIA Jetson is a series of embedded computing boards from NVIDIA designed specifically for AI applications. These boards integrate a CPU, GPU, and AI accelerator to expedite machine learning applications.

Aetina’s Edge Devices are built on NVIDIA Jetson to ensure optimal performance in terms of end-to-end acceleration for AI applications, all within an energy-efficient design. NVIDIA Jetson allows users to perform real-time data analysis thanks to its edge computing capabilities.

Felipe emphasizes that when we talk about embedded computing, we can replace “embedded” with “edge.” While “embedded” refers to computing performed within a larger system, “edge” computing highlights that the computation occurs closer to the data source, often directly within the device itself. Therefore, NVIDIA Jetson is ideal for edge computing purposes.

Currently, NVIDIA Jetson not only features the necessary hardware characteristics but also comes equipped with a comprehensive software suite called “Jetson Platform Services,” now part of JetPack 6.0 (the latest SDK released by NVIDIA in 2024). This suite offers a complete solution for building end-to-end accelerated AI applications.

NVIDIA Jetson VS Traditional IPC: the key differences

Several key features set NVIDIA Jetson apart from traditional Industrial PCs (IPCs), making it a suitable choice for a range of AI applications and beyond.

• Specialization for AI Applications: NVIDIA Jetson is specifically designed for AI applications, both in hardware and software. The integration of a GPU and AI accelerator ensures efficient processing of AI tasks. In contrast, traditional IPCs are more suited for general-purpose non-AI applications. However, due to its GPU capabilities, NVIDIA Jetson can also handle non-AI tasks, such as 3D image rendering.
• AI Computing Power: NVIDIA Jetson Orin series offers exceptional computing power, measured in TOPS (Tera Operations Per Second). The Jetson Orin Nano 4GB delivers up to 20 TOPS, the Orin NX provides up to 70 TOPS, and the AGX Orin reaches an impressive 275 TOPS. On the contrary, traditional IPCs typically do not come with integrated AI acceleration capabilities equivalent to the NVIDIA Jetson modules. In order to achieve comparable AI performance, they would require high-end GPU cards, resulting in higher power consumption (approximately 4x times higher) and larger form factors.
• Form Factor: A typical Jetson module is significantly smaller than the smallest available IPC motherboard (which measures approximately 146 x 120 mm). NVIDIA Jetson comes in a small form factor, making it suitable for various applications such as traffic monitoring and smart agriculture. For example, the Jetson Orin Nano module measures 45 x 70 mm, making it highly compact and suitable for edge applications.

  Visual comparison between the smallest IPC motherboard (146 x 120 mm) and the NVIDIA Jetson Orin Nano module (70 x 45 mm)

• Power Efficiency and Cost: NVIDIA Jetson is more power-efficient and cost-effective compared to IPCs. The NVIDIA Jetson AGX Orin 64GB, for instance, consumes only 130W to deliver 275 TOPS, whereas a traditional IPC would need over 500W to achieve similar AI performance due to the requirement of high-end GPUs. Additionally, Jetson modules are generally more affordable since they integrate the necessary CPU, GPU, and AI accelerators, eliminating the need for costly separate graphic cards.
• Privacy Concerns: NVIDIA Jetson processes data at the edge, significantly reducing privacy concerns compared to IPCs that rely on cloud connectivity for processing. This edge computing capability ensures that sensitive data is analyzed and stored locally, enhancing data privacy and security.

What really makes NVIDIA Jetson series stand out, though, is the availability of several AI Development Toolsets, which make it the best choice for deep learning and machine learning applications. This includes several factors:

• Ecosystem Partners: NVIDIA has an extensive network of ecosystem partners, including distributors, ISVs, software services, camera providers, and hardware & design services like Aetina.
• Developer Community: NVIDIA supports a robust developer community where experts and peers can assist with questions on topics such as CUDA, TensorRT, and deep learning.
• AI Frameworks: While IPCs rely on general-purpose environments, Jetson is optimized with specialized tools and hardware acceleration for AI applications. Among these, the JetPack SDK stands out: Jetson Platform Services evolved from Metropolis Microservices, providing a comprehensive set of tools including DeepStream, TensorRT, and CUDA. This allows developers to start with ready-made modules rather than building from scratch.
• Aetina’s Board Support Package: One of the key features of Aetina’s NVIDIA Jetson-powered devices (DeviceEdge series) is our custom Board Support Package (BSP) patch, specifically developed for Aetina’s boards. This includes additional I/O connections and specific drivers not found in the original NVIDIA development kit.

All these elements make NVIDIA Jetson the most suitable solution for applications like agriculture, fish farming, medical, robotics, smart cities, and traffic control (read more on potential uses here: Edge AI in Smart Agriculture, Edge AI in Smart Transportation, client stories)

Getting Started with NVIDIA Jetson

According to Felipe, getting started with NVIDIA Jetson depends on your company’s level of development and software knowledge. If your company lacks a clear picture of how to develop applications, the first step is to explore existing NVIDIA models to understand the capabilities and determine the right device for your needs.

Choosing the right device involves defining the required computing power, measured in TOPS (Tera Operations Per Second). For lower computing power needs, the Jetson Orin Nano 4GB offers up to 20 TOPS. For mid-range applications, the Jetson Orin NX provides up to 70 TOPS, and for high-performance requirements, the Jetson AGX Orin delivers up to 275 TOPS. These decisions should be guided by a proof of concept (PoC) to ensure the selected device meets the specific application requirements.

If you are starting from scratch, partnering with an Independent Software Vendor (ISV) can expedite development. Typically, transitioning from PoC to a full solution takes 6 to 12 months, but with Jetson Platform Services, this timeline can be reduced to just a few months.

Advancements in AI and Edge Computing with NVIDIA Jetson

Finally, we asked Felipe for his perspective on the advancements of AI and Edge Computing, particularly how he foresees the development of AI through the NVIDIA Jetson series. He highlighted three main points:

• Scalability: NVIDIA Jetson devices are designed with scalability in mind. The current lineup, including the AGX Orin, Orin NX, and Orin Nano, ranges from lower performance at 20 TOPS to high performance at 275 TOPS. This range ensures that Jetson devices can meet a variety of performance needs. With a lifecycle extending up to January 2030, these devices promise longevity and ongoing support, making them a reliable choice for long-term projects.
• Real-Time Processing: Real-time processing is crucial for industries benefiting from machine vision and AI applications. NVIDIA Jetson’s powerful GPUs enable on-premise, real-time data processing, eliminating the need for cloud connectivity and significantly enhancing data privacy. This capability is particularly beneficial for applications that require immediate insights and local data processing, such as automated inspection, smart cities, and autonomous machines.
• Future Developments: Looking ahead, advancements such as 5G connectivity will significantly enhance data transfer capabilities between units, enabling more efficient remote deployment and improved redundancy. For example, deploying two AGX Orin units simultaneously could enable parallel analysis or serve as a failover solution. This setup ensures continuous operation without downtime, a critical development for many customers seeking robust and reliable AI solutions.

NVIDIA Jetson’s advancements in AI and edge computing continue to drive innovation, making it a compelling choice for industrial applications. With its superior AI capabilities, power efficiency, and scalability, Jetson is poised to lead the market in AI-powered edge computing solutions.

A summary of differences:

Below is a summary of all the differences between NVIDIA Jetson Orin series and traditional Industrial PCs:

About Felipe

Felipe Leiva writes about Edge AI Technology and its practical applications in everyday scenarios. Serving as a Technical Project Manager at Aetina, he brings over twenty years of experience in the technology industry. Felipe's expertise lies in leading key technical initiatives and training for EMEA key accounts, reflecting his deep commitment to advancing the field of Edge AI. His extensive engineering background and hands-on approach have positioned him as a knowledgeable voice in this rapidly evolving domain.

About Aetina Europe BV

Aetina, a provider of state-of-the-art AI solutions, offers a wide range of AI computing systems, platforms, hardware, and software tools ideal for the creation of different types of vertical AI. Aetina’s integrated solutions empower its Arm, x86 computers, GPUs, ASIC hardware, cloud management software, and development tools with artificial intelligence, delivering comprehensive, tailor-made hardware and software suites to enable smooth, quick system intellectualization progress at the edge. With its ecosystem network, Aetina makes the creation and deployment of any specific AI-powered applications highly achievable by leveraging its global partners’ AI technologies.