Incorporating PGO into a GitHub Actions workflow

Build locally with make

PGO can be integrated into a Makefile and continuous integration (CI) systems using simple command-line instructions, as shown in the sample Makefile below.

Use a text editor to create a file named Makefile containing the following content:

    

        
        
# Simple Makefile for building and benchmarking div_bench with and without PGO

# Compiler and flags
CXX := g++
CXXFLAGS := -O3 -std=c++17
LDLIBS := -lbenchmark -lpthread

# Default target: build both binaries
.PHONY: all clean clean-gcda clean-perf run
all: div_bench.base div_bench.opt

# Build the baseline binary (no PGO)
div_bench.base: div_bench.cpp
	$(CXX) $(CXXFLAGS) $< $(LDLIBS) -o $@

# Build the PGO-optimized binary:
# Note: This target depends on the source file and cleans previous profile data first.
# It runs the instrumented binary to generate new profile data before the final compilation.
div_bench.opt: div_bench.cpp
	$(MAKE) clean-gcda # Ensure no old profile data interferes
	$(CXX) $(CXXFLAGS) -fprofile-generate $< $(LDLIBS) -o $@
	@echo "Running instrumented binary to gather profile data..."
	./div_bench.opt # Generate .gcda file
	$(CXX) $(CXXFLAGS) -fprofile-use $< $(LDLIBS) -o $@ # Compile using the generated profile
	$(MAKE) clean-perf # Optional: Clean perf data if generated elsewhere

# Remove profile data files
clean-gcda:
	rm -f ./*.gcda

# Remove perf data files (if applicable)
clean-perf:
	rm -f perf-division-*

# Remove all generated files including binaries and profile data
clean: clean-gcda clean-perf
	rm -f div_bench.base div_bench.opt

# Run both benchmarks with informative headers
run: all # Ensure binaries are built before running
	@echo "==================== Without Profile-Guided Optimization ===================="
	./div_bench.base
	@echo "==================== With Profile-Guided Optimization ===================="
	./div_bench.opt

    

You can run the following commands in your terminal:

• make all (or simply make): Compiles both div_bench.base (without PGO) and div_bench.opt (with PGO). This includes the steps of generating profile data for the optimized version.
• make run: Builds both binaries (if they don’t exist) and then runs them, displaying the benchmark results for comparison.
• make clean: Removes the compiled binaries (div_bench.base, div_bench.opt) and any generated profile data files (*.gcda).

Build with GitHub Actions

Alternatively, you can integrate PGO into your Continuous Integration (CI) workflow using GitHub Actions. The YAML file below provides a basic example that compiles and runs the benchmark on a GitHub-hosted Ubuntu 24.04 Arm-based runner. This setup can be extended with automated tests to check for performance regressions.

    

        
        
name: PGO Benchmark

on:
  push:
    branches: [ main ]

jobs:
  build:
    runs-on: ubuntu-24.04-arm

    steps:
      - name: Check out source
        uses: actions/checkout@v3

      - name: Install dependencies
        run: |
          sudo apt-get update
          sudo apt-get install -y libbenchmark-dev g++

      - name: Clean previous profiling data
        run: |
          rm -rf ./*gcda
          rm -f div_bench.base div_bench.opt

      - name: Compile base and instrumented binary
        run: |
          g++ -O3 -std=c++17 div_bench.cpp -lbenchmark -lpthread -o div_bench.base
          g++ -O3 -std=c++17 -fprofile-generate div_bench.cpp -lbenchmark -lpthread -o div_bench.opt

      - name: Generate profile data and compile with PGO
        run: |
          ./div_bench.opt
          g++ -O3 -std=c++17 -fprofile-use div_bench.cpp -lbenchmark -lpthread -o div_bench.opt

      - name: Run benchmarks
        run: |
            echo "==================== Without Profile-Guided Optimization ===================="
            ./div_bench.base
            echo "==================== With Profile-Guided Optimization ===================="
            ./div_bench.opt
            echo "==================== Benchmarking complete ===================="

    

To use this workflow, save the YAML content into a file named pgo_benchmark.yml (or any other .yml name) inside the .github/workflows/ directory of your GitHub repository. Ensure your div_bench.cpp file is present in the repository root. When you push changes to the main branch, GitHub Actions will automatically detect this workflow file and execute the defined steps on an Arm-based runner, compiling both versions of the benchmark and running them.