It is recommended to use -O3 -mtune=native to achieve maximum speed during LightGBM training.
Using Intel Ivy Bridge CPU on 1M x 1K Bosch dataset, the performance increases as follow:
| Compilation Flag | Performance Index |
|---|---|
-O2 -mtune=core2 |
100.00% |
-O2 -mtune=native |
100.90% |
-O3 -mtune=native |
102.78% |
-O3 -ffast-math -mtune=native |
100.64% |
You can find more details on the experimentation below:
- Laurae++/Benchmarks
- Laurae2/gbt_benchmarks
- Laurae's Benchmark Master Data (Interactive)
- Kaggle Paris Meetup #12 Slides
The image below compares the runtime for training with different compiler options to a baseline using LightGBM compiled with -O2 --mtune=core2. All three options are faster than that baseline. The best performance was achieved with -O3 --mtune=native.
