hardware-counters

Hardware counters measure cache miss rates and branch mispredictions by collecting PMU events with tools like `perf stat`, computing key indicators, and correlating events to source code for low-level microarchitectural tuning.

CPU performance profiling with PMU events monitors hardware performance counters to pinpoint bottlenecks related to cache, branches, and memory access, enabling detailed microarchitectural performance tuning for performance-critical applications.

Identify slow C++ application loops by measuring L3 cache misses and branch mispredictions per instruction using `perf annotate`, correlating hardware performance events directly to specific lines of source code.

Yes, the PAPI library collects specific hardware performance monitoring unit (PMU) events alongside `perf stat`, gathering hardware counters to compute performance indicators like Instructions Per Clock (IPC) and cache miss rates.

The best way to analyze IPC and CPU bottlenecks is using hardware counters to collect PMU events, calculating Instructions Per Clock (IPC) metrics to pinpoint cache and memory access limitations for microarchitectural optimization.

Hardware counters are needed for low-level optimization when you must deeply analyze CPU performance to pinpoint bottlenecks related to cache, branches, and memory access that standard profiling cannot detect.