Benchmarking Suite for IREE Kernels

Setup

If you are not using a local iree build, install the iree pip packages:

pip install --find-links https://iree.dev/pip-release-links.html iree-compiler iree-runtime --upgrade

Create a python environment and install the requirements for the project:

python3.11 -m venv bench_venv
source bench_venv/bin/activate
pip install -r requirements.txt
pip install --no-compile --pre --upgrade -e common_tools
pip install iree-turbine@git+https://github.com/iree-org/iree-turbine.git@main

Performance

Pick any of the following kernels to test through IREE. Refer to the respective problems.py file in the folder to see which shapes are being tested.

Convolution Benchmarking

python convbench/conv_bench.py

GEMM Benchmarking

python gemmbench/gemm_bench.py

TK GEMM Benchmarking

python gemmbench/gemm_bench.py --tk

Attention Benchmarking

python attentionbench/attention_bench.py

Roofline

If you want to generate a roofline plot, you can call any of the suites for now with the --roofline option (provide a commma seperated list if you want to generate for multiple benchmarks combined):

python convbench/conv_bench.py --roofline results/iree_conv.csv,results/iree_attention.csv --plot results/attn_conv.png

If you want to generate a roofline plot for a certain data type, model, or batch size you can do:

python attentionbench/attention_bench.py --roofline results/iree_attention --plot results/attn_conv_bs1_fp8_unet.png --model unet --dtype f8E4M3FNUZ --batch 1