This directory contains tuned configurations for different settings of the fused_moe kernel.
For different settings of
- E (number of experts)
- N (intermediate size)
- device_name (torch.cuda.get_device_name())
the JSON file contains a mapping from M (batch size) to the chosen configuration.

The example configurations provided are for the Mixtral model for TP2 on H100
and TP4 on A100. Mixtral has intermediate size N = 14336, i.e. for TP2 we have
N = 7168 and for TP4 we have N = 3584.

Please feel free to tune the configurations using scripts in `benchmarks/kernels/benchmark_moe.py`
Some of the configurations files are copied from the SGLang repository. Thank you!
