A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 6, 23:00 UTC
Add tuned H100 MoE configs for LFM2 8B and 24B (#36699)
tianshu-Michael-yu committed
Mar 10, 2026 at 21:22 UTC
a197eda9c3d1174ee31c4da8f8b302bddfb7f08a
2 files changed
+166
vllm/model_executor/layers/fused_moe/configs/E=32,N=1792,device_name=NVIDIA_H100_80GB_HBM3.json
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+11
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+{
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+ "triton_version": "3.6.0",
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+ "512": {
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+ "BLOCK_SIZE_M": 64,
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+ "BLOCK_SIZE_N": 128,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 64,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ }
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+}
vllm/model_executor/layers/fused_moe/configs/E=64,N=1536,device_name=NVIDIA_H100_80GB_HBM3.json
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+{
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+ "triton_version": "3.6.0",
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+ "1": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 16,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "2": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 64,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 16,
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+ "num_warps": 4,
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+ "num_stages": 4
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+ },
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+ "4": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 64,
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+ "BLOCK_SIZE_K": 256,
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+ "GROUP_SIZE_M": 16,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "8": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 32,
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+ "BLOCK_SIZE_K": 256,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 4,
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+ "num_stages": 2
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+ },
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+ "16": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 32,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 16,
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+ "num_warps": 4,
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+ "num_stages": 5
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+ },
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+ "24": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 128,
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+ "BLOCK_SIZE_K": 256,
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+ "GROUP_SIZE_M": 32,
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+ "num_warps": 4,
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+ "num_stages": 2
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+ },
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+ "32": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "48": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "64": {
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+ "BLOCK_SIZE_M": 16,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "96": {
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+ "BLOCK_SIZE_M": 32,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "128": {
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+ "BLOCK_SIZE_M": 32,
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+ "BLOCK_SIZE_N": 128,
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+ "BLOCK_SIZE_K": 128,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "256": {
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+ "BLOCK_SIZE_M": 64,
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+ "BLOCK_SIZE_N": 64,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 4,
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+ "num_stages": 3
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+ },
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+ "512": {
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+ "BLOCK_SIZE_M": 128,
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+ "BLOCK_SIZE_N": 128,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 8,
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+ "num_stages": 3
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+ },
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+ "1024": {
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+ "BLOCK_SIZE_M": 128,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 8,
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+ "num_stages": 4
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+ },
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+ "1536": {
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+ "BLOCK_SIZE_M": 128,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 8,
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+ "num_stages": 4
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+ },
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+ "2048": {
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+ "BLOCK_SIZE_M": 128,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 8,
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+ "num_stages": 4
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+ },
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+ "3072": {
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+ "BLOCK_SIZE_M": 128,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 32,
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+ "num_warps": 8,
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+ "num_stages": 4
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+ },
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+ "4096": {
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+ "BLOCK_SIZE_M": 128,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 8,
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+ "num_stages": 4
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+ },
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+ "8192": {
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+ "BLOCK_SIZE_M": 128,
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+ "BLOCK_SIZE_N": 256,
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+ "BLOCK_SIZE_K": 64,
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+ "GROUP_SIZE_M": 1,
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+ "num_warps": 8,
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+ "num_stages": 4
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+ }
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+}