A Graphics Processing Unit (GPU) is a specialized electronic processor designed to accelerate parallel computations, particularly those involving graphics rendering, matrix operations, and large-scale data processing. Unlike a CPU, which prioritizes sequential task execution, a GPU contains thousands of smaller cores optimized for simultaneous processing.
Also Known As
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Graphics card processor
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Video processor
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Parallel processor
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Accelerator chip
How It Works
A GPU is built with a massively parallel architecture.
It divides large workloads into thousands of smaller threads that execute concurrently.
Modern GPUs are programmable and support compute frameworks such as NVIDIA CUDA and OpenCL.
They are commonly installed on expansion cards or embedded directly into processors.
Key Characteristics
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Thousands of lightweight cores
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Optimized for matrix math
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High memory bandwidth
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Designed for throughput over latency
Common Use Cases
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Deep learning training
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3D rendering
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Video encoding and decoding
GPU vs CPU
| Feature | GPU | CPU |
|---|---|---|
| Core Count | Thousands | 4–64 |
| Best For | Parallel workloads | Sequential logic |
| AI Training | Highly optimized | Limited efficiency |
Benefits
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Accelerates AI workloads
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Handles massive parallel tasks
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Improves rendering performance
Limitations
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Not ideal for branching logic
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Requires specialized programming
Frequently Asked Questions
What is a GPU used for?
A GPU is used for rendering graphics, accelerating AI training, and processing large parallel workloads.
Is a GPU faster than a CPU?
For parallel tasks like matrix computations, a GPU is significantly faster. For sequential tasks, a CPU performs better.
Related Terms
