Graphics Processing Unit (GPU) – The Powerhouse of Visual Computing

The Graphics Processing Unit (GPU) is a specialized electronic circuit designed to handle graphics rendering, image processing, and parallel computing. Initially, GPUs were primarily used for rendering images and videos, but modern GPUs are also used for tasks like gaming, artificial intelligence (AI), deep learning, cryptocurrency mining, and scientific simulations.

1. Functions of a GPU

A GPU is responsible for processing graphical data and displaying it on a monitor. It performs several key functions:

(A) Graphics Rendering

• Converts raw data into visual images.
• Uses techniques like rasterization, shading, and anti-aliasing to create high-quality visuals.

(B) Parallel Processing

• Unlike a CPU (which has a few powerful cores), a GPU has hundreds or thousands of smaller cores that handle multiple tasks simultaneously.
• This makes GPUs ideal for machine learning, AI, and large-scale computations.

2. Types of GPUs

There are two main types of GPUs:

(A) Integrated GPU

• Built into the CPU (like Intel UHD Graphics, AMD Radeon Vega).
• Power-efficient but not ideal for high-performance gaming or AI.

(B) Dedicated GPU (Discrete GPU)

• A separate hardware component with its own VRAM (Video RAM) and cooling system.
• Examples: NVIDIA GeForce, AMD Radeon, NVIDIA Quadro, AMD Radeon Pro.

3. GPU Architecture & Components

(A) CUDA Cores / Stream Processors

• The processing units inside a GPU that handle computing tasks.

(B) VRAM (Video RAM)

• Dedicated memory for storing textures, shaders, and rendering data.

4. GPU Performance Factors

(A) Clock Speed (MHz/GHz)

• Determines how fast a GPU processes data.

(B) VRAM Capacity (GB)

• 4GB VRAM – Basic gaming and video editing.

5. GPU Applications Beyond Gaming

• Artificial Intelligence & Deep Learning (NVIDIA Tesla, RTX)
• Cryptocurrency Mining (Ethereum mining uses GPU processing power)