AMD Radeon Vega 8 Embedded
About GPU
The AMD Radeon Vega 8 Embedded GPU is an integrated graphics solution designed for use in low-power devices such as laptops, mini PCs, and embedded systems. With a base clock speed of 300MHz and a boost clock speed of 1100MHz, the Radeon Vega 8 offers decent performance for a variety of tasks, including light gaming, photo and video editing, and general multimedia consumption.
One of the key features of the Radeon Vega 8 is its 512 shading units, which allow for smooth and efficient rendering of graphics. The GPU also has a 15W thermal design power (TDP), making it well-suited for use in small form factor devices with limited cooling capabilities.
In terms of memory, the Radeon Vega 8 utilizes system shared memory, which means it can dynamically allocate and use a portion of the system's RAM for graphics processing. While this may not offer the same level of performance as dedicated VRAM, it allows for greater flexibility and cost savings in integrated graphics solutions.
The theoretical performance of the Radeon Vega 8 is rated at 1.126 TFLOPS, which is respectable for an integrated GPU in this power class. This level of performance makes the Radeon Vega 8 well-suited for everyday tasks such as web browsing, media consumption, and light gaming, making it a versatile option for entry-level and budget-friendly devices.
Overall, the AMD Radeon Vega 8 Embedded GPU offers a good balance of performance, power efficiency, and versatility, making it a solid choice for a wide range of small form factor and embedded systems.
Basic
Label Name
AMD
Platform
Integrated
Launch Date
February 2018
Model Name
Radeon Vega 8 Embedded
Generation
Great Horned Owl
Base Clock
300MHz
Boost Clock
1100MHz
Bus Interface
IGP
Memory Specifications
Memory Size
System Shared
Memory Type
System Shared
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.
System Shared
Memory Clock
SystemShared
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.
System Dependent
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.
8.800 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.
35.20 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.
2.253 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.
70.40 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.
1.103
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.
512
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.
1.2
OpenCL Version
2.1
Benchmarks
FP32 (float)
Score
1.103
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS