AMD Radeon Pro Vega 56
About GPU
The AMD Radeon Pro Vega 56 GPU is a high-performance graphics card designed for professional use in demanding applications such as video editing, 3D rendering, and CAD/CAM software. With a base clock of 1138MHz and a boost clock of 1250MHz, this GPU provides fast and efficient performance for handling complex tasks.
With 8GB of HBM2 memory and a memory clock speed of 786MHz, the Radeon Pro Vega 56 offers ample memory and high bandwidth for handling large datasets and textures. The 3584 shading units and 4MB of L2 cache further enhance the GPU's ability to process and render graphics quickly and accurately.
One of the standout features of the AMD Radeon Pro Vega 56 is its 8.96 TFLOPS theoretical performance, which translates to smooth and responsive real-time rendering and simulation of complex visual effects.
In terms of power consumption, the GPU has a TDP of 210W, which is relatively high but can be justified given its high performance capabilities. When it comes to compatibility, the AMD Radeon Pro Vega 56 is designed for mobile platforms, making it well-suited for professional users who require a powerful GPU in a portable workstation.
Overall, the AMD Radeon Pro Vega 56 GPU is a top-tier graphics card that delivers exceptional performance for professional applications. Its high memory capacity, fast clock speeds, and efficient shading units make it a valuable asset for professionals in need of a reliable and capable graphics solution.
Basic
Label Name
AMD
Platform
Mobile
Launch Date
August 2017
Model Name
Radeon Pro Vega 56
Generation
Radeon Pro Mac
Base Clock
1138MHz
Boost Clock
1250MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
8GB
Memory Type
HBM2
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.
2048bit
Memory Clock
786MHz
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.
402.4 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.
80.00 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.
280.0 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.
17.92 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.
560.0 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.
8.781
TFLOPS
Miscellaneous
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.
3584
L1 Cache
16 KB (per CU)
L2 Cache
4MB
TDP
210W
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
2.1
Benchmarks
FP32 (float)
Score
8.781
TFLOPS
Blender
Score
521
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender