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Update shapes in microbenchmarks to reflect more realistic data #3438

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Update shapes in microbenchmarks to reflect more realistic data #3438

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8 changes: 5 additions & 3 deletions benchmarks/dashboard/microbenchmark_quantization_config.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -10,9 +10,11 @@ output_dir: "benchmarks/microbenchmarks/results"
model_params:
- name: "small_bf16_linear"
matrix_shapes:
- name: "small_sweep"
min_power: 10
max_power: 15
- name: "llama4"
- name: "deepseek_v3_236b"
- name: "deepseek_v3_671b"
- name: "qwen3_32b"
- name: "gemma3_27b"
high_precision_dtype: "torch.bfloat16"
torch_compile_mode: "max-autotune"
device: "cuda"
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49 changes: 48 additions & 1 deletion benchmarks/microbenchmarks/benchmark_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,53 @@ def get_shapes_for_config(
"ffn.w2": (M, 3584, 8192),
}
shapes.extend([(f"{name}_{k}", v) for k, v in llama_shapes.items()])
elif name == "llama4":
# LLaMa 4 shapes
llama4_shapes = [
("FFN", (16384, 8192, 5120)),
("QO_proj", (16384, 8192, 8192)),
("KV_proj", (16384, 8192, 1024)),
("FFN", (128000, 8192, 5120)),
("QO_proj", (128000, 8192, 8192)),
("KV_proj", (128000, 8192, 1024)),
]
shapes.extend([(f"{name}_{k}", v) for k, v in llama4_shapes])
elif name == "deepseek_v3_236b":
# DeepSeek V3 236B shapes
deepseek_v3_236b_shapes = [
("FFN", (16384, 1536, 5120)),
("QKVO_proj", (16384, 7168, 7168)),
("FFN", (128000, 1536, 5120)),
("QKVO_proj", (128000, 7168, 7168)),
]
shapes.extend([(f"{name}_{k}", v) for k, v in deepseek_v3_236b_shapes])
elif name == "deepseek_v3_671b":
# DeepSeek V3 671B shapes
deepseek_v3_671b_shapes = [
("FFN", (16384, 2048, 7168)),
("QKVO_proj", (16384, 7168, 7168)),
("FFN", (128000, 2048, 7168)),
("QKVO_proj", (128000, 7168, 7168)),
]
shapes.extend([(f"{name}_{k}", v) for k, v in deepseek_v3_671b_shapes])
elif name == "qwen3_32b":
# Qwen3 32B shapes
qwen3_32b_shapes = [
("QO_proj", (16384, 5120, 5120)),
("KV_proj", (16384, 5120, 640)),
("QO_proj", (128000, 5120, 5120)),
("KV_proj", (128000, 5120, 640)),
]
shapes.extend([(f"{name}_{k}", v) for k, v in qwen3_32b_shapes])
elif name == "gemma3_27b":
# Gemma3 27B shapes
gemma3_27b_shapes = [
("QO_proj", (16384, 4096, 4096)),
("KV_proj", (16384, 4096, 1024)),
("QO_proj", (128000, 4096, 4096)),
("KV_proj", (128000, 4096, 1024)),
]
shapes.extend([(f"{name}_{k}", v) for k, v in gemma3_27b_shapes])
elif name == "pow2":
# Generate shapes with dimensions that are powers of 2
min_power_of_2 = shape_config.get("min_power", 10) # 1024
Expand Down Expand Up @@ -105,7 +152,7 @@ def get_shapes_for_config(
counter += 1
else:
raise NotImplementedError(
f"Shape config {name} not supported. Supported options: custom, llama, pow2, pow2_extended, sweep."
f"Shape config {name} not supported. Supported options: custom, llama, llama4, deepseek_v3_236b, deepseek_v3_671b, qwen3_32b, gemma3_27b, pow2, pow2_extended, sweep."
)
return shapes

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