Asynchronous Batching Boosts GPU Inference 22%

A GPU inference optimization using asynchronous batching via CUDA streams and events achieves 22% throughput improvement by overlapping CPU batch preparation with active GPU computation, eliminating idle cycles without modifying inference kernels. High relevance for teams optimizing LLM serving infrastructure.