NVIDIA RTX A500 Embedded
About GPU
The NVIDIA RTX A500 Embedded GPU is a powerful and efficient option for professional use. With a base clock of 1192MHz and a boost clock of 1627MHz, this GPU can handle demanding tasks with ease. Its 4GB of GDDR6 memory and 1750MHz memory clock ensure quick data access and smooth performance.
The RTX A500 features 2048 shading units and 2MB of L2 cache, allowing for complex calculations and rendering. Its TDP of 35W makes it suitable for embedded systems where power consumption is a concern. Despite its lower power usage, the GPU still offers impressive theoretical performance, delivering 6.664 TFLOPS of computational power.
One of the standout features of the NVIDIA RTX A500 is its support for real-time ray tracing and AI-enhanced workflows, thanks to its RT and Tensor Cores. This capability makes it an excellent choice for professionals working in industries such as engineering, design, and content creation.
Overall, the NVIDIA RTX A500 Embedded GPU is a reliable and high-performance option for professionals who require a balance of power and efficiency. Its support for advanced technologies, combined with its impressive specs, makes it a compelling choice for embedded systems and applications where reliable GPU performance is crucial. Whether used for medical imaging, edge AI, or other professional applications, the RTX A500 delivers the performance and features needed to handle demanding workloads.
Basic
Label Name
NVIDIA
Platform
Professional
Model Name
RTX A500 Embedded
Generation
Quadro Mobile
Base Clock
1192MHz
Boost Clock
1627MHz
Bus Interface
PCIe 4.0 x16
Memory Specifications
Memory Size
4GB
Memory Type
GDDR6
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.
64bit
Memory Clock
1750MHz
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.
112.0 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.
78.10 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.
104.1 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.
6.664 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.
104.1 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.
6.531
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.
16
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
L1 Cache
128 KB (per SM)
L2 Cache
2MB
TDP
35W
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
6.531
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS