Performance Analysis and Asynchronous Operations

Define arithmetic intensity and use it to classify a kernel as compute-bound or memory-bound.

Use NVIDIA Nsight Compute to profile a kernel and identify primary performance bottlenecks.

Calculate a kernel's achieved memory bandwidth and compute throughput from profiler metrics.

Construct a roofline model for a given GPU and plot a kernel's performance to visualize its bottleneck.

Apply an iterative optimization methodology: profile, identify bottleneck, formulate a hypothesis, implement an optimization, and re-profile.

Use CUDA streams to manage asynchronous operations and overlap kernel execution with data transfers.

Use CUDA events to accurately time kernel execution and measure the effectiveness of stream overlap.