# IREE Benchmark Suites

> :exclamation: The TensorFlow benchmarks were disabled in
[#12758](https://github.com/openxla/iree/pull/12758/) in the interest of
severing the build dependency on TF. It should be possible to re-enable some /
all of the tests with a bit of effort.

**We are in the progress of replacing the legacy benchmark suites. Currently the
new benchmark suites only support `x86_64`, `CUDA`, and `compilation statistics`
benchmarks. For working with the legacy benchmark suites, see
[IREE Benchmarks (Legacy)](/benchmarks/README.md)**.

IREE Benchmarks Suites is a collection of benchmarks for IREE developers to
track performance improvements/regressions during development.

The benchmark suites are run for each commit on the main branch and the results
are uploaded to https://perf.iree.dev for regression analysis (for the current
supported targets). On pull requests, users can write `benchmarks:
x86_64,cuda,comp-stats` (or a subset) at the bottom of the PR descriptions and
re-run the CI workflow to trigger the benchmark runs. The results will be
compared with https://perf.iree.dev and post in the comments.

Information about the definitions of the benchmark suites can be found in the
[IREE Benchmark Suites Configurations](/build_tools/python/benchmark_suites/iree/README.md).

## Running Benchmark Suites Locally

### Prerequisites

Install `iree-import-tf` and `iree-import-tflite` in your Python environment
(see
[Tensorflow Integration](https://openxla.github.io/iree/getting-started/tensorflow/)
and
[TFLite Integration](https://openxla.github.io/iree/getting-started/tflite/)).

### Build Benchmark Suites

Configure IREE with `-DIREE_BUILD_E2E_TEST_ARTIFACTS=ON`:

```sh
cmake -GNinja -B "${IREE_BUILD_DIR}" -S "${IREE_REPO}" \
  -DCMAKE_BUILD_TYPE=RelWithDebInfo \
  -DCMAKE_C_COMPILER=clang \
  -DCMAKE_CXX_COMPILER=clang++ \
  -DIREE_ENABLE_LLD=ON \
  -DIREE_BUILD_E2E_TEST_ARTIFACTS=ON
```

Build the benchmark suites and tools:

```sh
cmake --build "${IREE_BUILD_DIR}" --target \
  iree-e2e-test-artifacts \
  iree-benchmark-module
```

### Run Benchmarks

Export the execution benchmark config:

```sh
build_tools/benchmarks/export_benchmark_config.py execution > exec_config.json
```

Run benchmarks (currently only support running on a Linux host):

```sh
build_tools/benchmarks/run_benchmarks_on_linux.py \
  --normal_benchmark_tool_dir="${IREE_BUILD_DIR}/tools" \
  --e2e_test_artifacts_dir="${IREE_BUILD_DIR}/e2e_test_artifacts" \
  --execution_benchmark_config=exec_config.json \
  --target_device_name="<target_device_name, e.g. c2-standard-16>" \
  --output=benchmark_results.json \
  --verbose \
  --cpu_uarch="<host CPU uarch, e.g. CascadeLake>"
# Traces can be collected by adding:
# --traced_benchmark_tool_dir="${IREE_TRACED_BUILD_DIR}/tools" \
# --trace_capture_tool=/path/to/iree-tracy-capture \
# --capture_tarball=captured_tracy_files.tar.gz
```

Note that:

-   `<target_device_name>` selects a benchmark group targets a specific device:
    -   Common options:
        -   `c2-standard-16` for x86_64 CPU benchmarks.
        -   `a2-highgpu-1g` for NVIDIA GPU benchmarks.
    -   All device names are defined under
        [build_tools/python/e2e_test_framework/device_specs](/build_tools/python/e2e_test_framework/device_specs).
-   To run x86_64 benchmarks, right now `--cpu_uarch` needs to be provided and
    only `CascadeLake` is available currently.
-   To build traced benchmark tools, see
    [Profiling with Tracy](/docs/developers/developing_iree/profiling_with_tracy.md).

Filters can be used to select the benchmarks:

```sh
build_tools/benchmarks/run_benchmarks_on_linux.py \
  --normal_benchmark_tool_dir="${IREE_BUILD_DIR}/tools" \
  --e2e_test_artifacts_dir="${IREE_BUILD_DIR}/e2e_test_artifacts" \
  --execution_benchmark_config=exec_config.json \
  --target_device_name="c2-standard-16" \
  --output=benchmark_results.json \
  --verbose \
  --cpu_uarch="CascadeLake" \
  --model_name_regex="MobileBert*" \
  --driver_filter_regex='local-task' \
  --mode_regex="4-thread"
```

### Generate Compilation Statistics (Compilation Benchmarks)

Export the compilation benchmark config:

```sh
build_tools/benchmarks/export_benchmark_config.py compilation > comp_config.json
```

Generate the compilation statistics:

```sh
build_tools/benchmarks/collect_compilation_statistics.py \
  alpha \
  --compilation_benchmark_config=comp_config.json \
  --e2e_test_artifacts_dir="${IREE_BUILD_DIR}/e2e_test_artifacts" \
  --build_log="${IREE_BUILD_DIR}/.ninja_log" \
  --output=compile_stats_results.json
```

Note that you need to use [Ninja](https://ninja-build.org/) to build the
benchmark suites as the tool collects information from its build log.

### Show Execution / Compilation Benchmark Results

See
[Generating Benchmark Report](/build_tools/benchmarks/README.md#generating-benchmark-report).

### Find Compile and Run Commands to Reproduce Benchmarks

Each benchmark has its benchmark ID in the benchmark suites, you will see a
benchmark ID at:

-   In the serie's URL of https://perf.iree.dev
    -   Execution benchmark: `https://perf.iree.dev/serie?IREE?<benchmark_id>`
    -   Compilation benchmark:
        `https://perf.iree.dev/serie?IREE?<benchmark_id>-<metric_id>`
-   In `benchmark_results.json` and `compile_stats_results.json`
    -   Execution benchmark result has a field `run_config_id`
    -   Compilation benchmark result has a field `gen_config_id`
-   In PR benchmark summary or the markdown generated by
    `diff_local_benchmarks.py`, each benchmark has the link to its
    https://perf.iree.dev URL, which includes the benchmark ID.

If you don't have aritfacts locally, see
[Fetching Benchmark Artifacts from CI](#fetching-benchmark-artifacts-from-ci) to
find the GCS directory of the CI artifacts. Then fetch the needed files:

```sh
export GCS_URL="gs://iree-github-actions-<presubmit|postsubmit>-artifacts/<run_id>/<run_attempt>"
export E2E_TEST_ARTIFACTS_DIR="e2e_test_artifacts"

# Download all artifacts
mkdir "${E2E_TEST_ARTIFACTS_DIR}"
gcloud storage cp -r "${GCS_URL}/e2e-test-artifacts" "${E2E_TEST_ARTIFACTS_DIR}"

# Download benchmark configs
gcloud storage cp "${GCS_URL}/benchmark-config.json" exec_config.json
gcloud storage cp "${GCS_URL}/compilation-config.json" comp_config.json
```

Run the helper tool to dump benchmark commands from benchmark configs:

```sh
build_tools/benchmarks/benchmark_helper.py dump-cmds \
  --execution_benchmark_config=exec_config.json \
  --compilation_benchmark_config=comp_config.json \
  --e2e_test_artifacts_dir="${E2E_TEST_ARTIFACTS_DIR}" \
  --benchmark_id="<benchmark_id>"
```

### Get Full List of Benchmarks

The commands below output the full list of execution and compilation benchmarks,
including the benchmark names and their flags:

```sh
build_tools/benchmarks/export_benchmark_config.py execution > exec_config.json
build_tools/benchmarks/export_benchmark_config.py compilation > comp_config.json
build_tools/benchmarks/benchmark_helper.py dump-cmds \
  --execution_benchmark_config=exec_config.json \
  --compilation_benchmark_config=comp_config.json
```

## Fetching Benchmark Artifacts from CI

#### 1. Find the corresponding CI workflow run

On the commit of the benchmark run, you can find the list of the workflow jobs
by clicking the green check mark. Click the `Details` of job
`build_e2e_test_artifacts`:

![image](https://user-images.githubusercontent.com/2104162/223781032-c22e2922-2bd7-422d-abc2-d6ef0d31b0f8.png)

#### 2. Get the GCS directory of the built artifacts

On the job detail page, expand the step `Uploading e2 test artifacts`, you will
see a bunch of lines like below. The
URL`gs://iree-github-actions-<presubmit|postsubmit>-artifacts/<run_id>/<run_attempt>/`
is the directory of artifacts:

```
Copying file://build-e2e-test-artifacts/e2e_test_artifacts/iree_MobileBertSquad_fp32_module_fdff4caa105318036534bd28b76a6fe34e6e2412752c1a000f50fafe7f01ef07/module.vmfb to gs://iree-github-actions-postsubmit-artifacts/4360950546/1/e2e-test-artifacts/iree_MobileBertSquad_fp32_module_fdff4caa105318036534bd28b76a6fe34e6e2412752c1a000f50fafe7f01ef07/module.vmfb
...
```

#### 3. Fetch the benchmark artifacts

To fetch files from the GCS URL, the gcloud CLI tool
(https://cloud.google.com/sdk/docs/install) can list the directory contents and
download files (see https://cloud.google.com/sdk/gcloud/reference/storage for
more usages). If you want to use CI artifacts to reproduce benchmarks locally,
see
[Find Compile and Run Commands to Reproduce Benchmarks](#find-compile-and-run-commands-to-reproduce-benchmarks).

Set the GCS directory URL from the step
[2. Get the GCS directory of the built artifacts](#2-get-the-gcs-directory-of-the-built-artifacts):

```sh
export GCS_URL="gs://iree-github-actions-<presubmit|postsubmit>-artifacts/<run_id>/<run_attempt>"
```

Download artifacts:

```sh
# The GCS directory has the same structure as your local ${IREE_BUILD_DIR}/e2e_test_artifacts.
gcloud storage ls "${GCS_URL}/e2e-test-artifacts"

# Download all source and imported MLIR files:
gcloud storage cp "${GCS_URL}/e2e-test-artifacts/*.mlir" "<target_dir>"
```

Execution and compilation benchmark configs can be downloaded at:

```sh
# Execution benchmark config:
gcloud storage cp "${GCS_URL}/benchmark-config.json" exec_config.json

# Compilation benchmark config:
gcloud storage cp "${GCS_URL}/compilation-config.json" comp_config.json
```

Benchmark raw results and traces can be downloaded at:

```sh
# Benchmark raw results
gcloud storage cp "${GCS_URL}/benchmark-results/benchmark-results-*.json" .

# Benchmark traces
gcloud storage cp "${GCS_URL}/benchmark-results/benchmark-traces-*.tar.gz" .
```