How can caching mechanisms be optimized for high-throughput inference

Question

Can you tell me How can caching mechanisms be optimized for high-throughput inference?

Answer 1

You can optimize caching mechanisms for high-throughput inference by using an LRU (Least Recently Used) cache to store frequently accessed model outputs and avoid redundant computations.

Here is the code snippet below:

In the above code, we are using the following key points:

• lru_cache from functools to store and reuse previous inference results for high-throughput processing.

• Efficient cache size management through the maxsize argument.

Hence, this caching mechanism minimizes redundant computations, boosting throughput and optimizing performance.