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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define data parallelism in your own words.
💡 Hint: Think about how teams might divide a project.
Question 2
Easy
What is the main advantage of model parallelism?
💡 Hint: Consider the resources available to each machine.
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 data parallelism?
- A method of splitting a model across nodes
- Processing data across multiple nodes simultaneously
- A method of distributing tasks among users
💡 Hint: Focus on how the data is divided.
Question 2
True or False: Model parallelism is used when a model can fit into a single machine's memory.
- True
- False
💡 Hint: Think of the model's size in relation to memory.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a distributed machine learning system for training a large image classification model. Specify how you would implement both data and model parallelism.
💡 Hint: Consider how large datasets and models will be divided to maintain efficiency.
Question 2
Evaluate a distributed machine learning framework and discuss the strengths and weaknesses of its data and model parallelism strategies.
💡 Hint: Look at how the framework uses both types of parallelism and theorize on their implications.
Challenge and get performance evaluation