What is JIT and AOT in machine learning?

What is the difference between JIT and AOT in machine learning?

JIT stands for Just-In-Time compilation, while AOT means Ahead-Of-Time compilation. JIT compiles code at runtime, optimizing performance based on actual usage, whereas AOT compiles code before execution, which can lead to faster startup times.

Can you give me examples of when to use JIT or AOT?

Sure! Use JIT when you need flexibility and performance optimization during execution, like in dynamic environments. AOT is better for applications where startup speed is critical, such as mobile apps.

What are the advantages of using JIT?

JIT offers improved performance through runtime optimizations, reduced memory usage, and the ability to adapt to changing workloads.

Are there any downsides to using AOT?

Yes, AOT can lead to longer build times and less flexibility since all optimizations are done before execution, which may not adapt well to varying workloads.