Practice Machine Learning on GPUs - 10.7.2 | 10. Vector, SIMD, GPUs | Computer Architecture
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does GPU stand for?

πŸ’‘ Hint: Think of how GPUs are used in gaming.

Question 2

Easy

Why are GPUs better suited for deep learning than CPUs?

πŸ’‘ Hint: Consider how many operations need to happen at once.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is a GPU primarily used for in machine learning?

  • Single-threaded processing
  • Parallel processing
  • Memory storage

πŸ’‘ Hint: Think about how many operations need to occur at once in ML tasks.

Question 2

True or False: GPUs can only be used for graphics rendering.

  • True
  • False

πŸ’‘ Hint: Consider the versatility of GPU applications.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Analyze how the performance of a deep learning model like a CNN would change if trained on a GPU instead of a CPU. Provide metrics such as training time, accuracy, and scalability.

πŸ’‘ Hint: Consider the computational demands of the model and how GPUs manage these demands.

Question 2

Discuss the potential challenges and limitations that arise when using GPUs for machine learning, particularly in terms of resource management and model complexity.

πŸ’‘ Hint: Think about both hardware and software aspects in machine learning.

Challenge and get performance evaluation