NVIDIA Jetson AGX Xavier GPU
The NVIDIA Jetson AGX Xavier GPU is an integrated platform that boasts impressive performance and efficiency for a wide range of applications. With a base clock of 854MHz and a boost clock of 1377MHz, this GPU delivers fast and reliable processing power. The system shared memory size and type, along with a memory clock, ensure efficient handling of data and tasks.
With 512 shading units and a 512KB L2 cache, the Jetson AGX Xavier GPU is capable of handling complex computations and graphics rendering with ease. Its low 30W TDP makes it an energy-efficient option for various use cases, helping to reduce power consumption without sacrificing performance.
The theoretical performance of 1.41 TFLOPS further demonstrates the GPU's capability to handle demanding workloads, making it suitable for AI, robotics, autonomous vehicles, and other compute-intensive applications.
In addition to its impressive technical specifications, the NVIDIA Jetson AGX Xavier GPU is known for its reliability and stability, providing a seamless user experience. Its compact and integrated design makes it easy to incorporate into various systems and devices, further adding to its appeal.
Overall, the NVIDIA Jetson AGX Xavier GPU offers exceptional performance, energy efficiency, and reliability, making it a top choice for developers and engineers looking to harness the power of GPU computing for their projects. Whether used for AI, deep learning, or other intensive tasks, this GPU delivers outstanding results.
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Basic
Label Name
NVIDIA
Platform
Integrated
Launch Date
October 2018
Model Name
Jetson AGX Xavier GPU
Generation
Tegra
Base Clock
854MHz
Boost Clock
1377MHz
Bus Interface
IGP
Transistors
9,000 million
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.
32
Foundry
TSMC
Process Size
12 nm
Architecture
Volta
Memory Specifications
Memory Size
System Shared
Memory Type
System Shared
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.
System Shared
Memory Clock
SystemShared
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.
System Dependent
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.
22.03 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.
44.06 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.
2.820 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.
705.0 GFLOPS
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.
1.382
TFLOPS
Miscellaneous
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.
8
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.
512
L1 Cache
128 KB (per SM)
L2 Cache
512KB
TDP
30W
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.
1.2
OpenCL Version
1.2
OpenGL
4.6
DirectX
12 (12_1)
CUDA
7.2
Shader Model
6.4
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.
16
Benchmarks
FP32 (float)
Score
1.382
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS