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Generate Flamegraph Using perf record and Flamegraph.pl

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Benchmark Programs Using time, perf stat, and hyperfine Profile with Valgrind Callgrind and View in KCachegrind

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2.0s Limit 256MB

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Implementation

Implement a program with measurable hotspots and generate flame graph.

Requirements:

Create a program with multiple functions of varying complexity
Include functions that consume measurable CPU time
Create nested function calls to show call stack depth
Use perf record to capture profile data
Process output with stackcollapse-perf.pl
Generate SVG flame graph using flamegraph.pl
Analyze the flame graph to identify hotspots
Demonstrate understanding of flame graph interpretation
Show before/after optimization comparison
Print instructions for generating flame graph

Why This Matters

Brendan Gregg invented flame graphs at Netflix to make raw perf record stack samples legible at a glance, and they're now the default hotspot view in Linux perf, py-spy, and async-profiler for the JVM. A single unexpectedly wide frame in a flame graph has driven real production fixes, from Netflix's encoding pipeline tuning to countless 'why is this container pegging the CPU' incidents.

Hints

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Validation Suite

main.c

Workspace 1.0

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