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[BE] [moe training] bench script for single device moe layer #3126

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[BE] [moe training] bench script for single device moe layer #3126

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danielvegamyhre
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  • Add bench script to benchmark MoE layer computation in isolation, without any distributed/comms aspects.
  • Configurable options:
    • num_experts
    • dim
    • hidden_dim
    • seq_len
    • local_batch_size
  • This is useful for benchmarking the computation portion of the MoE specifically, to iterate on quickly, without having to look at a trace to exclude all2all comms etc.
  • Profiling is included though, so the developer can quickly break down the specific quantization kernels, GEMMs etc

Llama4 17bx16e shapes

CUDA_VISIBLE_DEVICES=6 python benchmarks/prototype/moe_training/bench_moe_layer.py --recipe mxfp8 --local_batch_size=16 --dim=5120 --hidden_dim=8192 --local_num_experts=8
total_M: 131072, N: 8192, K: 5120
bf16 time: 275.270 ms
mxfp8 time: 192.420 ms
speedup: 1.431x

DeepSeekV3 671b shapes

CUDA_VISIBLE_DEVICES=6 python benchmarks/prototype/moe_training/bench_moe_layer.py --recipe mxfp8 --local_batch_size=16 --dim=7168 --hidden_dim=2048 --local_num_experts=8
total_M: 131072, N: 2048, K: 7168
bf16 time: 92.032 ms
mxfp8 time: 80.182 ms
speedup: 1.148x

@danielvegamyhre danielvegamyhre added topic: not user facing Use this tag if you don't want this PR to show up in release notes moe labels Oct 6, 2025
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pytorch-bot bot commented Oct 6, 2025 •
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3126

Note: Links to docs will display an error until the docs builds have been completed.

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@meta-cla meta-cla bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Oct 6, 2025
@danielvegamyhre danielvegamyhre changed the title [moe training] bench script for single device moe layer [BE] [moe training] bench script for single device moe layer Oct 11, 2025
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@danielvegamyhre
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