NVIDIA Jetson Orin Nano 8 GB
About GPU
The NVIDIA Jetson Orin Nano 8GB GPU is an impressive addition to the Jetson lineup, offering professional-grade performance in a compact and energy-efficient package. With 8GB of LPDDR5 memory and a memory clock of 1067MHz, the Orin Nano is capable of handling demanding workloads with ease.
One of the standout features of this GPU is its 1024 shading units, which allow for high-quality rendering and complex visual effects. Additionally, the 256KB L2 cache helps to minimize latency and improve overall system performance.
Despite its high performance capabilities, the Orin Nano is incredibly power-efficient, with a TDP of just 15W. This makes it an ideal choice for applications where power consumption is a concern, such as edge computing and robotics.
In terms of performance, the Orin Nano is capable of delivering a theoretical performance of 1.28 TFLOPS, making it well-suited for a wide range of professional workloads, including AI inferencing, computer vision, and robotics.
Overall, the NVIDIA Jetson Orin Nano 8GB GPU is an impressive piece of hardware that offers the perfect balance of performance, power efficiency, and compact form factor. Whether you're developing AI applications, running deep learning models, or creating advanced visual effects, the Orin Nano is a versatile and capable solution that's well worth considering.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
March 2023
Model Name
Jetson Orin Nano 8 GB
Generation
Tegra
Bus Interface
PCIe 4.0 x4
Memory Specifications
Memory Size
8GB
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.
128bit
Memory Clock
1067MHz
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.
68.29 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.
10.00 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.
20.00 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.
2.560 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.
640.0 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.
1.306
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.
1024
L1 Cache
128 KB (per SM)
L2 Cache
256KB
TDP
15W
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
1.306
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS