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AMD Radeon Vega 8

About GPU

The AMD Radeon Vega 8 is an integrated GPU that offers solid performance for laptops and budget desktop PCs. With a base clock of 300MHz and a boost clock of 2000MHz, the Vega 8 delivers smooth and responsive graphics for everyday tasks, as well as light gaming and content creation. One of the key features of the Vega 8 is its system shared memory, which allows for flexible memory allocation based on system needs. This means that the GPU can dynamically adjust its memory usage, providing optimal performance for different tasks without the need for dedicated VRAM. With 512 shading units and a TDP of 45W, the Vega 8 strikes a good balance between performance and power efficiency. It also offers a theoretical performance of 2.048 TFLOPS, making it suitable for casual gaming and multimedia applications. While the Vega 8 may not be as powerful as dedicated gaming GPUs, it excels at handling everyday computing tasks and light gaming. Its integrated design also makes it a cost-effective solution for budget-conscious consumers who want to enjoy decent graphics performance without breaking the bank. Overall, the AMD Radeon Vega 8 is a reliable and capable integrated GPU that offers good performance for its price point. Whether you're streaming videos, editing photos, or playing casual games, the Vega 8 delivers smooth and reliable graphics performance for everyday use.

Basic

Label Name

AMD

Platform

Integrated

Launch Date

January 2021

Model Name

Radeon Vega 8

Generation

Cezanne

Base Clock

300MHz

Boost Clock

2000MHz

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.

16.00 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.

64.00 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.

4.096 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.

128.0 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.

2.089 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

45W

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