AMD Radeon Pro Vega II
The AMD Radeon Pro Vega II is a powerful GPU designed for desktops, offering exceptional performance for professional workloads. With a base clock of 1574MHz and a boost clock of 1720MHz, this GPU delivers impressive speed and efficiency for demanding tasks such as 3D rendering, video editing, and high-resolution graphics design.
One of the standout features of the Radeon Pro Vega II is its massive 32GB of HBM2 memory, providing ample space for large datasets and complex simulations. The memory clock of 806MHz ensures rapid data access, while the 4096 shading units and 4MB L2 cache contribute to smooth, lag-free performance.
With a TDP of 475W, the Radeon Pro Vega II is a power-hungry GPU, but its theoretical performance of 14.09 TFLOPS more than justifies its energy consumption. Professionals in fields such as animation, engineering, and scientific research will appreciate the GPU's ability to handle compute-intensive tasks with ease.
Overall, the AMD Radeon Pro Vega II is an excellent choice for professionals who require high levels of performance and reliability from their GPU. Its impressive specifications and robust design make it well-suited for demanding work environments, and its ability to tackle complex workloads with speed and precision make it a valuable asset for content creators, designers, and engineers. If you're in need of a top-of-the-line GPU for your professional endeavors, the Radeon Pro Vega II is definitely worth considering.
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Basic
Label Name
AMD
Platform
Desktop
Launch Date
June 2019
Model Name
Radeon Pro Vega II
Generation
Radeon Pro Mac
Base Clock
1574MHz
Boost Clock
1720MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
32GB
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.
4096bit
Memory Clock
806MHz
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.
825.3 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.
110.1 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.
440.3 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.
28.18 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.
880.6 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.
14.372
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.
4096
L1 Cache
16 KB (per CU)
L2 Cache
4MB
TDP
475W
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
14.372
TFLOPS
Blender
Score
876
Vulkan
Score
100987
OpenCL
Score
99542
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender
Vulkan
OpenCL