triton-operator-performance-eval

Diagnose Triton kernel performance bottlenecks on Ascend NPUs by analyzing msprof data to evaluate function-level and operator-level metrics, classifying issues as Memory-Bound or Compute-Bound, and generating optimization suggestions.

Ascend NPU Triton kernel profiling requires msprof tooling data covering function-level and operator-level metrics, alongside access to specific kernel names for msprof op commands to accurately evaluate hardware utilization across diverse shapes and precisions.

Evaluate Triton kernel performance across different input shapes and precisions by applying msprof profiling data to identify memory usage and compute efficiency variations, enabling direct performance comparison and targeted optimization for diverse workload configurations.

msprof op profiling classifies Triton kernel bottlenecks by analyzing operator-level metrics to determine if performance limitations are Memory-Bound or Compute-Bound, outputting structured metrics that directly guide memory usage and compute efficiency optimization strategies.

Profiling Triton kernels on Ascend NPUs requires prerequisite msprof tooling and explicit access to kernel names for msprof op execution, meaning unregistered or unsupported custom kernels cannot be automatically profiled without providing exact naming identifiers.