Practice Techniques For Optimizing Efficiency In Ai Circuits (5.3) - Techniques for Optimizing Efficiency and Performance in AI Circuits

Practice: Techniques for Optimizing Efficiency in AI Circuits

Lesson 5.3Techniques for Optimizing Efficiency and Performance in AI Circuits

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8 questions

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2 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
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6 sample questions

Question 1.
What does GPU stand for?
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Think of a component that renders graphics but is used for calculations.
Question 2.
What is data parallelism?
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How do we manage large datasets in parallel?
3Question 3.
What does TPU stand for?
- Tensor Processing Unit
- Temporary Processing Unit
- Tensor Program Unit
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Think of what type of processing happens for AI models.
4Question 4.
True or False: Data parallelism allows for processing large datasets simultaneously.
- True
- False
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Think about how data can be handled in multiple parts.
Question 5.
Design a small AI application that benefits from using both a GPU and a TPU. How would you structure the workload?
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Think about the strengths of each hardware unit.
Question 6.
Discuss the potential trade-offs when reducing precision in AI computations. How does this affect model performance?
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Consider the balance between speed and accuracy.

4 more questions in this section. Enroll free to practise them all.