CPU & GPU Differences (HL)
What is a CPU?
The Central Processing Unit (CPU) is the main processor in a computer, designed for sequential task execution and complex logic processing.It is optimised for general-purpose computing, running applications, operating systems, and user inputs.
Comparison: CPU vs. GPU
| Feature | CPU (Central Processing Unit) | GPU (Graphics Processing Unit) |
|---|---|---|
| Processing Style | Sequential, optimised for logic and decision-making | Parallel, optimised for bulk computations |
| Core Count | Few, high-performance cores (2–64) | Thousands of smaller, less powerful cores |
| Best For | General-purpose computing (OS, applications, logic processing) | Graphics rendering, AI training, simulations |
| Memory Access | Low-latency, optimised for small data operations | High-bandwidth, optimised for large-scale data processing |
| Power Efficiency | Optimised for single-task execution, lower power consumption | Requires more power due to parallel execution |
CPUs and GPUs Working Together
Modern computing relies on CPU-GPU collaboration to maximise performance:
- Task Division: The CPU handles logic, program flow, and system-level instructions. The GPU is responsible for large-scale computations such as image processing or matrix operations.
- Data Sharing: The CPU sends large datasets (e.g. image frames, tensors) to the GPU for processing. After computation, the GPU returns the results (e.g. rendered frames or model outputs) back to the CPU for further handling or display.
- Execution Coordination: The system manages timing and communication between processors to prevent bottlenecks and ensure efficient use of both CPU and GPU resources.
- Example: In a video editing application, the CPU loads the video project, manages the user input, and organises logic. Simultaneously, the GPU performs real-time frame rendering, applies effects like blur and color correction, and encodes preview frames. The two work in tandem: the CPU organises tasks and the GPU accelerates heavy computation.
Key Takeaways
- The CPU is optimised for sequential processing, making it ideal for general-purpose computing.
- The GPU is designed for parallel computing, excelling in graphics rendering, AI, and large-scale simulations.
- CPUs have fewer but more powerful cores, while GPUs contain thousands of smaller cores optimised for bulk computation.
- CPUs and GPUs work together in modern computing to balance workloads efficiently.