GPU vs CPU inference tradeoffs in MLOps - Quick Revision & Key Differences

Recall & Review

beginner

What is the main advantage of using a GPU for machine learning inference?

GPUs can process many operations in parallel, making them faster for large, complex models during inference.

beginner

Why might CPUs be preferred over GPUs for some inference tasks?

CPUs are better for smaller models or when low latency for single requests is needed, and they use less power.

intermediate

How does batch size affect GPU inference performance?

Larger batch sizes improve GPU efficiency by using parallelism better, but increase latency per request.

intermediate

What is a tradeoff when using GPUs for inference in terms of cost?

GPUs are more expensive to run and maintain, so they may increase operational costs compared to CPUs.

intermediate

Explain why CPU inference might be more energy efficient than GPU inference.

CPUs consume less power for small or simple inference tasks, making them more energy efficient in those cases.

Which hardware is generally better for large batch inference?

A Both perform the same

B CPU

C GPU

D Neither is suitable

GPUs excel at processing large batches in parallel, improving throughput.

What is a common reason to choose CPU over GPU for inference?

A Low latency for single requests

B High power consumption

C Better parallel processing

D Higher cost

CPUs handle single requests with lower latency better than GPUs.

How does increasing batch size affect GPU inference latency?

A Latency decreases

B Latency stays the same

C Latency becomes zero

D Latency increases

Larger batches increase latency per request but improve throughput.

Which hardware typically costs more to operate for inference?

A GPU

B CPU

C Both cost the same

D Neither costs anything

GPUs have higher operational costs due to power and maintenance.

Why might CPU inference be more energy efficient?

A Because CPUs run at higher clock speeds

B Because CPUs use less power for small tasks

C Because CPUs have more cores

D Because CPUs are newer technology

CPUs consume less power when handling small or simple inference tasks.

Describe the main tradeoffs between using GPUs and CPUs for machine learning inference.

Think about speed, cost, and power use.

Explain how batch size influences the choice between GPU and CPU for inference.

Consider how many requests are processed at once.