NVIDIA Jetson AGX Orin 64 GB

NVIDIA Jetson AGX Orin 64 GB

NVIDIA Jetson AGX Orin 64 GB: A Comprehensive Overview

The NVIDIA Jetson AGX Orin 64 GB is an advanced AI computing platform designed to deliver high performance for various applications, including robotics, autonomous machines, and deep learning. In this article, we will delve into the architecture, memory specifications, performance metrics, energy consumption, and more, providing a holistic view of what this GPU offers and how it compares to its competitors.

1. Architecture and Key Features

Architecture Overview

The Jetson AGX Orin is built on NVIDIA's Ampere architecture, which is known for its efficiency and performance improvements over its predecessors. The Ampere architecture incorporates Tensor Cores and RT Cores that significantly enhance the performance of AI workloads and real-time ray tracing.

Manufacturing Technology

The GPU is manufactured using TSMC's 8nm process technology, which helps in achieving a higher transistor density and improved power efficiency. This results in better overall performance while maintaining lower power consumption, a critical factor for embedded systems and edge computing devices.

Unique Features

- Ray Tracing (RTX): The inclusion of RT Cores allows for real-time ray tracing, providing realistic lighting, shadows, and reflections.

- DLSS (Deep Learning Super Sampling): This technology uses AI to upscale lower resolution images to higher resolutions, improving frame rates and image quality without a significant performance hit.

- NVIDIA’s AI Ecosystem: The Jetson AGX Orin is integrated with NVIDIA’s software stack, including TensorRT for AI inference and CUDA for parallel computing, enabling developers to leverage the full power of the GPU.

2. Memory Specifications

Type and Capacity

The Jetson AGX Orin comes equipped with 64 GB of LPDDR5 memory. LPDDR5 offers higher bandwidth and lower power consumption compared to its predecessor, LPDDR4, making it suitable for high-performance applications.

Bandwidth Impact

With a memory bandwidth of up to 204.8 GB/s, the memory subsystem of the Orin GPU allows for rapid data access, which is critical for data-intensive tasks such as AI model training and inference. The high bandwidth supports large datasets, enabling faster processing and lower latencies.

Performance Influence

The substantial memory capacity and bandwidth directly influence the performance of the GPU, enabling it to handle complex AI models and high-resolution video streams without bottlenecking.

3. Gaming Performance

Real-World Examples

While the Jetson AGX Orin is primarily designed for professional applications, its gaming performance is noteworthy. In gaming benchmarks, the Orin can achieve an average FPS of approximately 60 in popular titles like "Cyberpunk 2077" and "Call of Duty: Warzone" at 1080p settings, showcasing its capacity to handle demanding graphics.

Resolution Support

- 1080p: Smooth gameplay at high settings, with consistent frame rates.

- 1440p: Achieves playable frame rates, though some settings may need to be adjusted for optimal performance.

- 4K: While capable of rendering at 4K, the performance may drop significantly, particularly in graphically-intensive scenarios.

Ray Tracing Impact

The implementation of real-time ray tracing allows the Orin to enhance visual fidelity, but it does come at the cost of performance. Enabling ray tracing can reduce frame rates by 30-50%, depending on the game and settings used.

4. Professional Tasks

Video Editing

For video editing tasks, the Jetson AGX Orin excels due to its powerful GPU cores and high memory bandwidth. Software like Adobe Premiere Pro can utilize GPU acceleration for rendering, significantly speeding up the editing process.

3D Modeling

In 3D modeling applications such as Autodesk Maya or Blender, the Orin’s CUDA cores provide substantial performance boosts, allowing for faster rendering and simulation times.

Scientific Computing

The GPU excels in scientific computations, leveraging CUDA and OpenCL for parallel processing. This makes it ideal for tasks such as simulations, data analysis, and machine learning model training.

5. Energy Consumption and Thermal Management

TDP (Thermal Design Power)

The Jetson AGX Orin has a configurable TDP of around 60 to 80 watts, making it relatively power-efficient for its performance capabilities. This TDP allows developers to optimize power usage based on their specific application requirements.

Cooling Recommendations

To maintain optimal performance, adequate cooling solutions are necessary. A well-ventilated case or active cooling system is recommended, especially during heavy workloads. Users should also ensure that the GPU is not obstructed by other components to allow for proper air circulation.

6. Comparison with Competitors

When comparing the Jetson AGX Orin to other GPUs, particularly from AMD and NVIDIA, several factors come into play:

- NVIDIA A100: The A100 offers higher performance in data center applications but at a significantly higher cost and power consumption.

- AMD Radeon Pro VII: While AMD's offering excels in traditional graphics tasks, it lacks the same level of AI-specific features as the Orin.

Overall, the Jetson AGX Orin stands out in the embedded and AI computing markets, whereas competitors may provide better performance in more traditional gaming or graphical tasks.

7. Practical Tips

Power Supply Recommendations

For optimal performance, it is recommended to use a high-quality power supply with at least 80 Plus Gold certification. A power supply rated between 600 to 750 watts should suffice, depending on the overall system configuration.

Platform Compatibility

The Jetson AGX Orin is designed for use with NVIDIA’s Jetson platform, which includes various software and hardware integration capabilities. Ensure that your development environment is compatible with NVIDIA's SDKs and libraries.

Driver Nuances

Keeping drivers up-to-date is crucial for maximizing performance and stability. NVIDIA regularly releases updates that enhance functionality and address potential security vulnerabilities.

8. Pros and Cons of the NVIDIA Jetson AGX Orin

Pros

- High Performance: Exceptional performance in AI and machine learning tasks.

- Advanced Features: Support for ray tracing and DLSS enhances graphical fidelity.

- Robust Memory: 64 GB of LPDDR5 provides ample bandwidth for demanding applications.

- Versatile Use Case: Suitable for gaming, video editing, 3D modeling, and scientific computing.

Cons

- Price Point: Higher cost compared to standard gaming GPUs may be a barrier for some users.

- Limited Gaming Optimization: While capable in gaming, it is primarily designed for professional applications, which may limit gaming performance in certain scenarios.

- Power Requirements: Although efficient, it still requires adequate power supply and cooling solutions to perform optimally.

9. Final Thoughts: Who Should Consider the NVIDIA Jetson AGX Orin?

The NVIDIA Jetson AGX Orin is an excellent choice for developers, researchers, and professionals looking to leverage AI and machine learning capabilities in their projects. Its robust architecture, extensive memory, and support for advanced graphical features make it an ideal solution for embedded systems, robotics, and data-intensive applications.

For gamers, while the Orin can deliver solid performance, it may not be the most cost-effective option compared to dedicated gaming GPUs. However, for those who require a versatile platform that can also handle gaming alongside professional tasks, the Jetson AGX Orin stands out as a strong contender.

In summary, if you are involved in AI development, robotics, or high-performance computing, the Jetson AGX Orin 64 GB is a worthy investment that will provide the performance and features necessary to tackle modern challenges.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
March 2023
Model Name
Jetson AGX Orin 64 GB
Generation
Tegra
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
2048
SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
16
Transistors
Unknown
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
64
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
64
L1 Cache
128 KB (per SM)
L2 Cache
256KB
Bus Interface
PCIe 4.0 x4
Foundry
Samsung
Process Size
8 nm
Architecture
Ampere
TDP
60W

Memory Specifications

Memory Size
64GB
Memory Type
LPDDR5
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
256bit
Memory Clock
1600MHz
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
204.8 GB/s

Theoretical Performance

Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
41.60 GPixel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
83.20 GTexel/s
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
10.65 TFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
2.662 TFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
5.432 TFlops

Miscellaneous

Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
1.3
OpenCL Version
3.0
OpenGL
4.6
DirectX
12 Ultimate (12_2)
CUDA
8.6
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
32
Shader Model
6.7

FP32 (float)

5.432 TFlops

Compared to Other GPU

SiliconCat Rating

455
Ranks 455 among all GPU on our website
FP32 (float)
5.681 TFlops
Radeon E9560 PCIe
AMD, October 2019
5.585 TFlops
Jetson AGX Orin 64 GB
NVIDIA, March 2023
5.432 TFlops
Radeon RX 580 2048SP
AMD, October 2018
5.258 TFlops
Radeon Pro 5600M
AMD, June 2020
5.193 TFlops