Home / AMD Radeon Vega 5: Performance and Specs

AMD Radeon Vega 5

AMD Radeon Vega 5 is a Integrated video accelerator from Intel. It began to be released in January 2020. The GPU has a boost frequency of 1400 MHz. It also has a memory frequency of DDR4-3200 / LPDDR4X-4266, platform dependent. Its characteristics, as well as benchmark results, are presented in more detail below.

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Basic

Label Name

Intel

Platform

Integrated

Launch Date

January 2020

Former Codename

Renoir

GPU Lithography

7 nm

Model Name

AMD Radeon Vega 5

Generation

Radeon RX Vega 4000/5000 Series

Base Clock

400 MHz

Boost Clock

1400 MHz

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.

320

RT Cores

Compute Units

Tensor Cores

Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.

TMUs

Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.

Bus Interface

Integrated

Foundry

TSMC

Process Size

7 nm

Architecture

Vega

TDP

Shared with processor; 10-25 W cTDP

Memory Specifications

Memory Size

Shared system memory

Memory Type

DDR4 / LPDDR4X shared system memory

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.

Dual-channel system memory, platform dependent

Memory Clock

DDR4-3200 / LPDDR4X-4266, platform dependent

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 memory dependent

Display and Media

AV1 Encode/Decode

No hardware support

H.264 Hardware Encode/Decode

Encode/Decode

H.265 HEVC Hardware Encode/Decode

Encode/Decode

H.266 VVC Hardware Encode/Decode

No hardware support

Intel Quick Sync Video

Outputs

HDMI, DisplayPort, USB-C DisplayPort Alt Mode; device 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.

11.2 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.

28 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.

1.79 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.

56 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.

0.9 TFlops

AI Features

Intel Deep Learning Boost on GPU

Miscellaneous

PCI Express Version

PCIe 3.0

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

1.2

OpenGL

4.6

CUDA

DirectX

12 (12_1)

Power Connectors

None

ROPs

The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.