What is pipe utilization?

Pipe utilization measures how effectively a kernel uses the execution resources within each Streaming Multiprocessor (SM) .

Each SM contains multiple independent execution pipes optimized for different instruction types - CUDA Cores for general floating-point arithmetic, Tensor Cores for tensor contractions, load/store units for memory access, and control flow units for branching. Pipe utilization shows what percentage of each pipeline's peak rate is being achieved when that pipe is actively executing at least one warp , averaged across all active SMs .

Before debugging application performance at the level of pipe utilization, GPU programmers should first consider GPU kernel utilization and SM utilization .

Pipe utilization is available in the the sm__inst_executed_pipe_*.avg.pct_of_peak_sustained_active metrics from NSight Compute (ncu), where the asterisk represents specific pipelines like fma , tensor , lsu , or adu (address).