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[Core][Kernel] Share persistent workspaces for Marlin and Humming (#57421)

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Signed-off-by: mgoin <mgoin64@gmail.com>
Co-authored-by: ErinYin <liang.yin@daocloud.io>
This commit is contained in:
Misha Goin
2026-09-20 17:28:33 +08:00
committed by GitHub
co-authored by ErinYin
parent 0e110f696d
commit e5fce7b56b
21 changed files with 598 additions and 211 deletions
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tests/kernels/quantization/test_marlin_tile_padding.py
+7 -6
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@@ -14,6 +14,7 @@ from vllm import _custom_ops as ops
from vllm.model_executor.layers.quantization.utils.marlin_utils import (
GPTQ_MARLIN_TILE,
apply_gptq_marlin_linear,
get_marlin_workspace,
marlin_make_empty,
marlin_make_workspace_new,
marlin_moe_padded_intermediate,
@@ -225,7 +226,7 @@ def test_fp8_marlin_padded_round_trip(shape, use_bias):
input=x,
weight=layer.weight,
weight_scale=layer.weight_scale,
workspace=layer.workspace,
workspace=get_marlin_workspace(layer.weight.device),
size_n=size_n,
size_k=size_k,
bias=layer.bias if use_bias else None,
@@ -288,7 +289,7 @@ def test_nvfp4_marlin_padded_round_trip(shape):
weight=layer.weight,
weight_scale=layer.weight_scale,
weight_global_scale=layer.weight_global_scale,
workspace=layer.workspace,
workspace=get_marlin_workspace(layer.weight.device),
size_n=size_n,
size_k=size_k,
)
@@ -392,7 +393,7 @@ def test_fp8_block_marlin_padded_round_trip(shape):
input=x,
weight=layer.weight,
weight_scale=layer.weight_scale_inv,
workspace=layer.workspace,
workspace=get_marlin_workspace(layer.weight.device),
size_n=size_n,
size_k=size_k,
bias=None,
@@ -440,7 +441,7 @@ def test_mxfp8_marlin_padded_round_trip(shape):
input=x,
weight=layer.weight,
weight_scale=layer.weight_scale,
workspace=layer.workspace,
workspace=get_marlin_workspace(layer.weight.device),
size_n=size_n,
size_k=size_k,
)
@@ -756,7 +757,7 @@ def test_fp8_marlin_moe_padded_round_trip(shape, quant):
topk_ids,
quant_type_id=scalar_types.float8_e4m3fn.id,
global_num_experts=e,
workspace=layer.workspace,
workspace=get_marlin_workspace(device),
)
with set_current_vllm_config(VllmConfig()):
ref = torch_experts(
@@ -833,7 +834,7 @@ def test_mxfp8_marlin_moe_padded_round_trip(shape):
topk_ids,
quant_type_id=scalar_types.float8_e4m3fn.id,
global_num_experts=e,
workspace=layer.workspace,
workspace=get_marlin_workspace(device),
)
with set_current_vllm_config(VllmConfig()):
ref = torch_experts(