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Advanced Topic 40 of 51 Computer Architecture & Logic

GPU Architecture

Massively parallel processors for throughput workloads.

How it works

A GPU has thousands of simple cores grouped into streaming multiprocessors that run thousands of threads in lockstep warps, hiding latency by switching threads.

Where it is used

Graphics, deep learning, simulations.

Common pitfall

Branch divergence within a warp and uncoalesced memory access slow it down.

Where it fits in the course

GPU Architecture is topic 40 of 51 in Computer Architecture & Logic, rated Advanced. It follows SIMD and Vector Processing. The next topic is DMA.

Practice and explore

How to study this topic

  1. Read the explanation above and restate the definition in your own words.
  2. Open the interactive lesson and answer its mini quiz.
  3. Read the common pitfall, then write a short example that avoids it.
  4. Check your understanding in the Computer Architecture & Logic quiz, and revisit the topic if you miss a question.

Frequently asked questions

What is GPU Architecture?
Massively parallel processors for throughput workloads. It belongs to Computer Architecture & Logic and is an advanced-level topic.
Where do people use GPU Architecture?
Graphics, deep learning, simulations.
What is the most common mistake with GPU Architecture?
Branch divergence within a warp and uncoalesced memory access slow it down.
What should I learn before this topic?
Start with SIMD and Vector Processing, the topic just before it in Computer Architecture & Logic.
How can I practice it?
Answer the mini quiz in the interactive lesson, then take the Computer Architecture & Logic quiz.
Is GPU Architecture hard to learn?
It is an Advanced topic. Expect to read the explanation more than once and to connect it with earlier topics. Working through a small example by hand helps most.
How long does it take to learn GPU Architecture?
Most learners can read the explanation and finish the interactive lesson in under an hour. Fluency comes from applying the idea, so plan a few short practice sessions with the quiz.
Which topics are related to GPU Architecture?
SIMD and Vector Processing, DMA, Cache Coherence are closely connected. The full list is in the related topics section of this page.
What should I study after GPU Architecture?
Continue with DMA, the next topic in Computer Architecture & Logic.

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