NVIDIA Jetson AGX Orin 32 GB
About GPU
The NVIDIA Jetson AGX Orin 32 GB GPU is an impressive addition to the NVIDIA line of professional GPUs. With a memory size of 32GB and memory type LPDDR5, this GPU offers fast and efficient performance for professional use. The memory clock of 1600MHz ensures smooth and quick data processing, making it ideal for a wide range of professional applications.
With 1792 shading units and 256KB L2 cache, the Jetson AGX Orin GPU delivers high-quality, detailed graphics and reliable performance. Its TDP of 40W ensures that it operates at a manageable power consumption level without sacrificing performance.
One of the standout features of the Jetson AGX Orin 32 GB GPU is its impressive theoretical performance of 3.333 TFLOPS. This makes it an excellent choice for demanding professional tasks such as deep learning, computer vision, robotics, and autonomous machines.
Overall, the NVIDIA Jetson AGX Orin 32 GB GPU is a powerful and versatile professional GPU that offers exceptional performance and efficiency. Its high memory size, fast memory type, and impressive theoretical performance make it a valuable asset for professionals in need of reliable and high-quality graphics processing. Whether used for AI, machine learning, or intensive graphics tasks, the Jetson AGX Orin GPU is sure to deliver outstanding results.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
February 2023
Model Name
Jetson AGX Orin 32 GB
Generation
Tegra
Bus Interface
PCIe 4.0 x4
Memory Specifications
Memory Size
32GB
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.
22.32 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.
52.08 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.
6.666 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.
1.667 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.
3.4
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.
14
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.
1792
L1 Cache
128 KB (per SM)
L2 Cache
256KB
TDP
40W
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
Benchmarks
FP32 (float)
Score
3.4
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS