AMD Radeon Pro Vega 64X
About GPU
The AMD Radeon Pro Vega 64X GPU is a powerful graphics processing unit designed for high-performance computing and graphical rendering tasks. With a base clock speed of 1250MHz and a boost clock speed of 1468MHz, this GPU is capable of handling demanding workloads with ease.
One of the standout features of the Radeon Pro Vega 64X is its impressive 16GB of HBM2 memory, which allows for smooth and efficient handling of large datasets and complex visualizations. The memory clock speed of 1000MHz further contributes to the GPU's exceptional performance, ensuring that it can handle even the most demanding tasks without breaking a sweat.
With 4096 shading units and 4MB of L2 cache, the Radeon Pro Vega 64X is able to deliver stunning visual experiences and uncompromising graphical fidelity. Additionally, the GPU's TDP of 250W ensures that it can deliver consistent performance under heavy workloads without overheating or throttling.
In terms of raw performance, the Radeon Pro Vega 64X is capable of delivering a theoretical performance of 12.03 TFLOPS, making it a compelling choice for professional users and content creators who require high levels of computational power.
Overall, the AMD Radeon Pro Vega 64X GPU is a top-tier graphics card that offers exceptional performance, advanced features, and ample memory capacity, making it an excellent choice for professionals in need of a high-performance GPU for demanding workloads.
Basic
Label Name
AMD
Platform
Mobile
Launch Date
March 2019
Model Name
Radeon Pro Vega 64X
Generation
Radeon Pro Mac
Base Clock
1250MHz
Boost Clock
1468MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
16GB
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
1000MHz
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.
512.0 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.
93.95 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.
375.8 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.
24.05 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.
751.6 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.
11.789
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
250W
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
11.789
TFLOPS
Blender
Score
624
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender