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New to C++ benchmarking? Check out our comprehensive guide: How to Benchmark C++ Code?
To use CodSpeed in your C++ codebase, you can use CodSpeed’s google_benchmark library, which is a compatibility layer to run both instrumented and walltime CodSpeed benchmarks.

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Writing benchmarks

CodSpeed integrates with the google_benchmark library. Here is a small example on how to declare benchmarks. Otherwise, any existing benchmarks of your project can be reused.
main.cpp
// Define the function under test
static void BM_StringCopy(benchmark::State &state) {
  std::string x = "hello";

  // Google benchmark relies on state.begin() and state.end() to run the benchmark and count iterations
  for (auto _ : state) {
    std::string copy(x);

    // Use DoNotOptimize and ClobberMemory to prevent the compiler optimizing away your benchmark
    // See: https://google.github.io/benchmark/user_guide.html#preventing-optimization
    benchmark::DoNotOptimize(copy);
    benchmark::ClobberMemory();
  }
}
// Register the benchmarked to be called by the executable
BENCHMARK(BM_StringCopy);

static void BM_memcpy(benchmark::State &state) {
  char *src = new char[state.range(0)];
  char *dst = new char[state.range(0)];
  memset(src, 'x', state.range(0));
  for (auto _ : state) {
    memcpy(dst, src, state.range(0));
    benchmark::DoNotOptimize(dst);
    benchmark::ClobberMemory();
  }
  delete[] src;
  delete[] dst;
}

BENCHMARK(BM_memcpy)->Range(8, 8 << 10);

// Entrypoint of the benchmark executable
BENCHMARK_MAIN();
Checkout the Google benchmark user guide for more advanced usage of the library.
Make sure that your benchmarks aren’t optimized away by the compiler by using benchmark::DoNotOptimize and benchmark::ClobberMemory. Checkout the Google benchmark user guide on preventing optimization for more information.

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Building & Running benchmarks

To build and run benchmarks, CodSpeed officially support usage of the google_benchmark library using both CMake and Bazel. If you are using another build system, you may find guidelines in the custom build systems section

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CMake

To use CodSpeed’s google_benchmark integration using CMake, you can declare a benchmark executable as follows:
CMakeLists.txt
cmake_minimum_required(VERSION 3.12)
include(FetchContent)

project(my_codspeed_project VERSION 0.0.0 LANGUAGES CXX)

# Enable release mode with debug symbols to display useful profiling data
set(CMAKE_BUILD_TYPE RelWithDebInfo)

set(BENCHMARK_DOWNLOAD_DEPENDENCIES ON)

FetchContent_Declare(
    google_benchmark
    GIT_REPOSITORY https://github.com/CodSpeedHQ/codspeed-cpp # Target the codspeed cpp repository
    SOURCE_SUBDIR google_benchmark # Make sure to target the google_benchmark subdirectory
    GIT_TAG main # Or chose a specific version or git ref, check the releases page on the repository
)

FetchContent_MakeAvailable(google_benchmark)

# Declare your benchmark executable and its sources here
add_executable(my_benchmark_executable benches/bench.cpp)

# Link your executable against the `benchmark::benchmark`, the `google_benchmark` library
# Note: the first argument must match the first argument of the `add_executable` call
target_link_libraries(my_benchmark_executable benchmark::benchmark)
Checkout the releases page if you want to target a specific version of the library.
This example is a dedicated CMakeLists.txt file for the benchmark executable. You can also add an executable target to your existing project’s CMakeLists.txt. Make sure to link this target against the benchmark::benchmark library.

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Building benchmarks

To build the benchmark executable, run:
terminal
$ mkdir build && cd build

$ cmake -DCODSPEED_MODE=simulation ..
-- The CXX compiler identification is GNU 14.2.1
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- ...
-- Configuring done (8.6s)
-- Generating done (0.1s)
-- Build files have been written to: /home/user/project-benchmark/build

$ make
[  1%] Building CXX object ...
 ...
 ...
[100%] Built target my_benchmark_executable

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The CODSPEED_MODE flag

Please note the -DCODSPEED_MODE=simulation flag in the cmake command. This will enable the CodSpeed CPU simulation mode for the benchmark executable, where each benchmark is run only once on a simulated CPU. If you omit the CODSPEED_MODE cmake flag, CodSpeed will not be enabled in the benchmark executable, and it will run as a regular benchmark. The CODSPEED_MODE cmake flag can take the following values:
  • off: defaulted to when the cmake flag is not provided, disables codspeed.
  • simulation: benchmarks are run only once on a simulated CPU.
  • walltime: used for walltime codspeed reports, see dedicated documentation
  • memory: benchmarks are run once using memory profiling
  • instrumentation: (deprecated) alias of simulation.

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Debug symbols

In order to get the most out of CodSpeed reports, debug symbols need to be enabled within your executable. In the example above, this is done by setting CMAKE_BUILD_TYPE to RelWithDebInfo.

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Running the benchmarks locally

Simply execute the compiled binary to run the benchmarks.
terminal
$ ./benchmark_example
Codspeed mode: simulation
2025-02-27T16:15:03+01:00
Running ./benchmark_example
Run on (12 X 4500 MHz CPUs)
CPU Caches:
  L1 Data 48 KiB (x6)
  L1 Instruction 32 KiB (x6)
  L2 Unified 1280 KiB (x6)
  L3 Unified 12288 KiB (x1) Load Average: 1.73, 1.71, 1.52
NOTICE: codspeed is enabled, but no performance measurement will be made since it's running in an unknown environment.
Checked: benches/main.cpp::BM_rand_vector
Checked: benches/main.cpp::BM_StringCopy
Checked: benches/main.cpp::BM_memcpy[8]
Checked: benches/main.cpp::BM_memcpy[64]
Checked: benches/main.cpp::BM_memcpy[512]
Checked: benches/main.cpp::BM_memcpy[4096]
Checked: benches/main.cpp::BM_memcpy[8192]
Congratulations ! 🎉 You can now run those benchmark in your CI to get the actual performance measurements.

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Running the benchmarks in your CI

To generate performance reports, you need to run the benchmarks in your CI. This allows CodSpeed to automatically run benchmarks and warn you about regressions during development.
If you want more details on how to configure the CodSpeed action, you can check out the Continuous Reporting section.
Here is an example of a GitHub Actions workflow that runs the benchmarks and reports the results to CodSpeed on every push to the main branch and every pull request:

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Running benchmarks in parallel CI jobs

If your benchmarks are taking too much time to run under the CodSpeed action, you can run them in parallel to speed up the execution. To parallelize your benchmarks, first split them in multiple executables that each run a subset of your benches.
CMakelists.txt
# Create individual benchmark executables
set(BENCHMARKS first_bench second_bench third_bench)

# Add `bench_name` target with `bench_name.cpp` source for each bench listed above
foreach(benchmark IN LISTS BENCHMARKS)
  add_executable(${benchmark} benches/${benchmark}.cpp)
  target_link_libraries(${benchmark}
    benchmark::benchmark
  )
endforeach()

# Create a custom target to run all benchmarks locally
add_custom_target(run_all_benchmarks
  COMMAND ${CMAKE_COMMAND} -E echo "Running all benchmarks..."
)
# Register each benchmark target as a dependency of
foreach(benchmark IN LISTS BENCHMARKS)
  add_custom_command(
    TARGET run_all_benchmarks
    POST_BUILD
    COMMAND ${CMAKE_COMMAND} -E echo "Running ${benchmark}..."
    COMMAND $<TARGET_FILE:${benchmark}>
    WORKING_DIRECTORY ${CMAKE_BINARY_DIR}
  )
endforeach()
Then update your CI workflow to run benchmarks executable by executable
To combine measurement modes like simulation and memory, check out the documentation on running multiple instruments serially.

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Bazel

You can also use CodSpeed’s google_benchmark integration with the Bazel integration.

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Building benchmarks

Import the library from the Bazel Central Registry in your MODULE.bazel file
MODULE.bazel
module(name = "my_module")
# Starting from 2.0.0, codspeed_google_benchmark_compat is available from the Bazel central registry
bazel_dep(name = "codspeed_google_benchmark_compat", version = "2.0.0")
Then, define your benchmark target in your packages’s BUILD.bazel file:
path/to/bench/BUILD.bazel
cc_binary(
    name = "my_benchmark", # Name of your benchmark target
    srcs = glob(["*.cpp", "*.hpp"]), # Or define sources however you wish
    deps = ["@codspeed_google_benchmark_compat//:benchmark"],
)
Finally, you can build the benchmarks by running:
terminal
$ bazel build //path/to/bench:my_benchmark \
    --@codspeed_google_benchmark_compat//:codspeed_mode=simulation --compilation_mode=dbg \
    --copt=-O2
INFO: Analyzed target //examples/google_benchmark:my_benchmark (0 packages loaded, 0 targets configured).
INFO: Found 1 target...
Target //examples/google_benchmark:my_benchmark up-to-date:
  bazel-bin/examples/google_benchmark/my_benchmark
INFO: Elapsed time: 0.138s, Critical Path: 0.00s
INFO: 1 process: 1 internal.
INFO: Build completed successfully, 1 total action

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Build options

As you may have noticed in the example, there are a few key build options essential for bazel to make full use of the CodSpeed library.
  • --@codspeed_google_benchmark_compat//:codspeed_mode=simulation enables the codspeed features of the library, which can take the following values here:
    • off: defaulted to when the cli flag is not provided, disables codspeed.
    • simulation: benchmarks are run only once on a simulated CPU.
    • walltime: used for walltime codspeed reports, see dedicated documentation
    • memory: benchmarks are run once using memory profiling
    • instrumentation: (deprecated) alias of simulation.
  • --compilation_mode=dbg: enables debug symbols in the compiled binary, used to generate meaningful CodSpeed reports.
  • --copt=-O2: sets the desired level of compiler optimizations in the benchmarks binary.
Setting default build optionsIf you do not want to specify these flags every time, you can create a .bazelrc file at the root of the bazel workspace with the following content
build --@codspeed_cpp//core:codspeed_mode=simulation
build --compilation_mode=dbg
build --copt=-O2

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Running the benchmarks locally

You can then run your benchmarks by running:
terminal
$ bazel run //path/to/bench:my_benchmark \
    --@codspeed_cpp//core:codspeed_mode=simulation
... Cached build step ...
Codspeed mode: simulation
2025-02-27T16:15:03+01:00
Running ./benchmark_example
Run on (12 X 4500 MHz CPUs)
CPU Caches:
  L1 Data 48 KiB (x6)
  L1 Instruction 32 KiB (x6)
  L2 Unified 1280 KiB (x6)
  L3 Unified 12288 KiB (x1) Load Average: 1.73, 1.71, 1.52
NOTICE: codspeed is enabled, but no performance measurement will be made since it's running in an unknown environment.
Checked: benches/main.cpp::BM_rand_vector
Checked: benches/main.cpp::BM_StringCopy
Checked: benches/main.cpp::BM_memcpy[8]
Checked: benches/main.cpp::BM_memcpy[64]
Checked: benches/main.cpp::BM_memcpy[512]
Checked: benches/main.cpp::BM_memcpy[4096]
Checked: benches/main.cpp::BM_memcpy[8192]

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Running the benchmarks in your CI

To generate performance reports, you need to run the benchmarks in your CI. This allows CodSpeed to automatically run benchmarks and warn you about regressions during development.
If you want more details on how to configure the CodSpeed action, you can check out the Continuous Reporting section.
Here is an example of a GitHub Actions workflow that runs the benchmarks and reports the results to CodSpeed on every push to the main branch and every pull request:
Separated build and run stepsNote that we separated the build and run steps in the CI workflow. This is important to speed up the CI workflow and avoiding instrumenting the build step.

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Custom build systems

If you need to have full control over your build system, here are guiding steps to take to use codspeed.

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Get the sources

Sources are located in the codspeed-cpp repository. You can either clone the repository, add it as a submodule or even download the sources as a zip file.

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Build the library

Sources of the google_benchmark CodSpeed integration library are located in the google_benchmark subdirectory. 3. Make sure the following pre-processor variables are defined when you build the library When building the library, the tricky part is to make sure google_benchmark’s fork has access to the codspeed-core library. Additionally, the following pre-processor variables must be defined:
  • CODPSEED_ENABLED: if not defined, google_benchmark will the same as the upstream library, with no CodSpeed features.
  • CODSPEED_SIMULATION: if running in simulation mode
    • Note: For versions prior to v2.0.0, use CODSPEED_INSTRUMENTATION instead.
  • CODSPEED_WALLTIME: if running in walltime mode
  • CODSPEED_ROOT_DIR: absolute path to the root directory of your project. This is used in the report to display file path relative to your root project
If you run into issues integrating CodSpeed’s google_benchmark library with your project, please reach out and open an issue on the codspeed-cpp repository.