Benchmark any WebGPU Kernel.
Check out /benches for an example, simply implement the Kernel trait and boom!
Provide a Python snippet to ensure that your kernel is correct!
Reproduce:
cat Cargo.toml
cargo bench --bench <bench_name>Results on M3 Max 14 core:
Naive Onepass (precision FAIL)
time: [88680.6021 ns 92554.9586 ns 95756.6363 ns]
thrpt: [40.7935 GiB/s 42.2047 GiB/s 44.0485 GiB/s]
Naive
time: [115698.3828 ns 116433.8667 ns 117343.1857 ns]
thrpt: [33.2891 GiB/s 33.5491 GiB/s 33.7624 GiB/s]
Naive Vectorized
time: [113990.1512 ns 114341.8859 ns 114775.5896 ns]
thrpt: [34.0338 GiB/s 34.1629 GiB/s 34.2683 GiB/s]
Welford Scalar
time: [74209.2818 ns 74668.5137 ns 75306.7653 ns]
thrpt: [51.8712 GiB/s 52.3146 GiB/s 52.6383 GiB/s]
Welford Vectorized
time: [48744.7028 ns 48831.9797 ns 48933.0603 ns]
thrpt: [79.8284 GiB/s 79.9937 GiB/s 80.1369 GiB/s]- Add throughput measurements
- Encode more commands into a single command buffer (philipturner/metal-flash-attention#12 (comment))
- Benchmark comparisons? Shared code between similar kernels?
- Simplify Kernel trait
- Cleaning & Polishing 🧽