Practice Principles Of Parallel Processing Architectures (7.2) - Parallel Processing Architectures for AI

Practice: Principles of Parallel Processing Architectures

Lesson 7.2Parallel Processing Architectures for AI

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10 questions

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3 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
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define SIMD.
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Think of a single process applied to many items at once.
Question 2.
What is task parallelism?
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Consider what happens when multiple jobs are done at the same time.
3Question 3.
What does SIMD stand for?
- Single Instruction
- Multiple Data
- Single Instruction
- Multiple Devices
- Simultaneous Instruction
- Multiple Data
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Focus on how the name indicates the relation between instructions and data.
4Question 4.
True or False: MIMD allows different processors to perform the same instruction on different data.
- True
- False
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Think of the flexibility of MIMD compared to SIMD.
Question 5.
Evaluate a parallel processing architecture for an AI task requiring simultaneous image and text analysis. Which model (SIMD or MIMD) would you choose and why?
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Consider the flexibility needed to process different types of instructions.
Question 6.
Design a scenario using data parallelism to reduce computation time for a deep learning model. Specify how tasks would be divided among processors.
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Think about dividing large datasets into smaller, manageable blocks for processing.

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