CSE Computer Science & Engineering Map The connected map of computing knowledge and engineering careers.
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Hardware → Computer Hardware

GPU

A specialized processor optimized for highly parallel computation, graphics workloads, and modern AI model training or inference.

Motivation

A GPU solves the problem of doing many simple computations at the same time. CPUs are optimized for flexible control flow, while GPUs are optimized for parallel throughput.

Mental model

Think of a CPU as a few powerful workers and a GPU as thousands of smaller workers doing similar work over large batches of data.

Where it fits

GPU belongs to the Hardware track, inside Computer Hardware. It connects hardware parallelism to product-level AI systems and software workloads such as neural networks.

Common mistakes

  • Thinking GPUs are only for graphics.
  • Assuming every program becomes faster on a GPU.
  • Ignoring data-transfer costs between CPU memory and GPU memory.

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