Optimizing Inference

Inference is the process of making predictions using a trained model. In Brain4J, inference performance can be significantly improved using batched inference.

Batch Inference

Instead of processing one input at a time, it's much more efficient to group multiple samples into a single batch. For example, predicting 100 inputs individually is slower and less efficient than predicting all 100 in a single batch.

This is because Brain4J executes tensor operations using multi-threaded routines that scale better with larger data chunks, reducing overhead and improving speed.

Next Steps

Check out Examples & Use Cases