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OpenDAS
vllm_cscc
Commits
a781e84e
Unverified
Commit
a781e84e
authored
Aug 27, 2025
by
Michael Goin
Committed by
GitHub
Aug 28, 2025
Browse files
[Perf] Tune configs for triton block fp8 gemm H100/H200 (#23748)
Signed-off-by:
mgoin
<
mgoin64@gmail.com
>
parent
1b7b161a
Changes
21
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Showing
20 changed files
with
1422 additions
and
433 deletions
+1422
-433
benchmarks/kernels/bench_block_fp8_gemm.py
benchmarks/kernels/bench_block_fp8_gemm.py
+113
-0
vllm/model_executor/layers/quantization/utils/configs/N=12288,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+146
-0
vllm/model_executor/layers/quantization/utils/configs/N=12288,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+146
-0
vllm/model_executor/layers/quantization/utils/configs/N=24576,K=1536,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+146
-0
vllm/model_executor/layers/quantization/utils/configs/N=24576,K=1536,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+146
-0
vllm/model_executor/layers/quantization/utils/configs/N=24576,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+33
-33
vllm/model_executor/layers/quantization/utils/configs/N=24576,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+35
-35
vllm/model_executor/layers/quantization/utils/configs/N=32768,K=512,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+22
-22
vllm/model_executor/layers/quantization/utils/configs/N=32768,K=512,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+24
-24
vllm/model_executor/layers/quantization/utils/configs/N=36864,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+32
-32
vllm/model_executor/layers/quantization/utils/configs/N=36864,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+34
-34
vllm/model_executor/layers/quantization/utils/configs/N=4096,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+146
-0
vllm/model_executor/layers/quantization/utils/configs/N=4096,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+146
-0
vllm/model_executor/layers/quantization/utils/configs/N=576,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
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vllm/model_executor/layers/quantization/utils/configs/N=576,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+43
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vllm/model_executor/layers/quantization/utils/configs/N=7168,K=16384,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+31
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vllm/model_executor/layers/quantization/utils/configs/N=7168,K=16384,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+33
-33
vllm/model_executor/layers/quantization/utils/configs/N=7168,K=18432,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+30
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vllm/model_executor/layers/quantization/utils/configs/N=7168,K=18432,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
...ame=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
+37
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vllm/model_executor/layers/quantization/utils/configs/N=7168,K=2048,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
..._H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
+38
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No files found.
benchmarks/kernels/bench_block_fp8_gemm.py
0 → 100644
View file @
a781e84e
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import
torch
from
vllm.model_executor.layers.quantization.utils.fp8_utils
import
(
w8a8_block_fp8_matmul
,
)
from
vllm.platforms
import
current_platform
from
vllm.triton_utils
import
triton
as
vllm_triton
assert
current_platform
.
is_cuda
(),
(
"Only support benchmarking w8a8 block fp8 kernel on CUDA device."
)
# DeepSeek-V3 weight shapes
DEEPSEEK_V3_SHAPES
=
[
(
512
+
64
,
7168
),
((
128
+
64
)
*
128
,
7168
),
(
128
*
(
128
+
128
),
512
),
(
7168
,
16384
),
(
7168
,
18432
),
(
18432
*
2
,
7168
),
(
24576
,
1536
),
(
12288
,
7168
),
(
4096
,
7168
),
(
7168
,
2048
),
]
def
build_w8a8_block_fp8_runner
(
M
,
N
,
K
,
block_size
,
device
):
"""Build runner function for w8a8 block fp8 matmul."""
factor_for_scale
=
1e-2
fp8_info
=
torch
.
finfo
(
torch
.
float8_e4m3fn
)
fp8_max
,
fp8_min
=
fp8_info
.
max
,
fp8_info
.
min
# Create random FP8 tensors
A_fp32
=
(
torch
.
rand
(
M
,
K
,
dtype
=
torch
.
float32
,
device
=
device
)
-
0.5
)
*
2
*
fp8_max
A
=
A_fp32
.
clamp
(
min
=
fp8_min
,
max
=
fp8_max
).
to
(
torch
.
float8_e4m3fn
)
B_fp32
=
(
torch
.
rand
(
N
,
K
,
dtype
=
torch
.
float32
,
device
=
device
)
-
0.5
)
*
2
*
fp8_max
B
=
B_fp32
.
clamp
(
min
=
fp8_min
,
max
=
fp8_max
).
to
(
torch
.
float8_e4m3fn
)
# Create scales
block_n
,
block_k
=
block_size
[
0
],
block_size
[
1
]
n_tiles
=
(
N
+
block_n
-
1
)
//
block_n
k_tiles
=
(
K
+
block_k
-
1
)
//
block_k
As
=
torch
.
rand
(
M
,
k_tiles
,
dtype
=
torch
.
float32
,
device
=
device
)
*
factor_for_scale
Bs
=
(
torch
.
rand
(
n_tiles
,
k_tiles
,
dtype
=
torch
.
float32
,
device
=
device
)
*
factor_for_scale
)
def
run
():
return
w8a8_block_fp8_matmul
(
A
,
B
,
As
,
Bs
,
block_size
,
torch
.
bfloat16
)
return
run
@
vllm_triton
.
testing
.
perf_report
(
vllm_triton
.
testing
.
Benchmark
(
x_names
=
[
"batch_size"
],
x_vals
=
[
1
,
16
,
64
,
128
,
256
,
512
,
1024
,
2048
,
4096
,
8192
,
16384
],
x_log
=
False
,
line_arg
=
"provider"
,
line_vals
=
[
"torch-bf16"
,
"w8a8-block-fp8"
],
line_names
=
[
"torch-bf16"
,
"w8a8-block-fp8"
],
ylabel
=
"TFLOP/s (larger is better)"
,
plot_name
=
"BF16 vs W8A8 Block FP8 GEMMs"
,
args
=
{},
)
)
def
benchmark_tflops
(
batch_size
,
provider
,
N
,
K
,
block_size
=
(
128
,
128
)):
M
=
batch_size
device
=
"cuda"
quantiles
=
[
0.5
,
0.2
,
0.8
]
if
provider
==
"torch-bf16"
:
a
=
torch
.
randn
((
M
,
K
),
device
=
device
,
dtype
=
torch
.
bfloat16
)
b
=
torch
.
randn
((
N
,
K
),
device
=
device
,
dtype
=
torch
.
bfloat16
)
ms
,
min_ms
,
max_ms
=
vllm_triton
.
testing
.
do_bench_cudagraph
(
lambda
:
torch
.
nn
.
functional
.
linear
(
a
,
b
),
quantiles
=
quantiles
)
else
:
# w8a8-block-fp8
run_w8a8
=
build_w8a8_block_fp8_runner
(
M
,
N
,
K
,
block_size
,
device
)
ms
,
min_ms
,
max_ms
=
vllm_triton
.
testing
.
do_bench_cudagraph
(
lambda
:
run_w8a8
(),
quantiles
=
quantiles
)
to_tflops
=
lambda
t_ms
:
(
2
*
M
*
N
*
K
)
*
1e-12
/
(
t_ms
*
1e-3
)
return
to_tflops
(
ms
),
to_tflops
(
max_ms
),
to_tflops
(
min_ms
)
if
__name__
==
"__main__"
:
block_size
=
(
128
,
128
)
for
N
,
K
in
DEEPSEEK_V3_SHAPES
:
print
(
f
"
\n
Benchmarking DeepSeek-V3, N=
{
N
}
K=
{
K
}
"
)
print
(
f
"TFLOP/s comparison (block_size=
{
block_size
}
):"
)
benchmark_tflops
.
run
(
print_data
=
True
,
# show_plots=False,
# save_path=f"bench_w8a8_block_fp8_tflops_n{N}_k{K}",
N
=
N
,
K
=
K
,
block_size
=
block_size
,
)
print
(
"
\n
Benchmark finished!"
)
vllm/model_executor/layers/quantization/utils/configs/N=12288,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
0 → 100644
View file @
a781e84e
{
"1"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"2"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"4"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
32
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"8"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
32
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"16"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
32
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"24"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"32"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"48"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"64"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"96"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"128"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"256"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"512"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"1024"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"1536"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"2048"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"3072"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"4096"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
4
}
}
vllm/model_executor/layers/quantization/utils/configs/N=12288,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
0 → 100644
View file @
a781e84e
{
"1"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
8
,
"num_stages"
:
4
},
"2"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"4"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"8"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
32
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"16"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
32
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
5
},
"24"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"32"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"48"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
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vllm/model_executor/layers/quantization/utils/configs/N=24576,K=1536,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
0 → 100644
View file @
a781e84e
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vllm/model_executor/layers/quantization/utils/configs/N=24576,K=1536,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
0 → 100644
View file @
a781e84e
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vllm/model_executor/layers/quantization/utils/configs/N=24576,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
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1
6
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6
4
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...
...
@@ -75,7 +75,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
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1
6
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"GROUP_SIZE_M"
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6
4
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4
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3
},
...
...
@@ -83,7 +83,7 @@
"BLOCK_SIZE_M"
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64
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"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
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32
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4
,
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3
},
...
...
@@ -91,7 +91,7 @@
"BLOCK_SIZE_M"
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64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
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128
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16
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4
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3
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...
...
@@ -107,7 +107,7 @@
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64
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:
128
,
"BLOCK_SIZE_K"
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128
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16
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4
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"num_stages"
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3
},
...
...
@@ -115,15 +115,15 @@
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64
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"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
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128
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"GROUP_SIZE_M"
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64
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32
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4
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4
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"2048"
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64
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4
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"num_stages"
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3
},
...
...
@@ -133,13 +133,13 @@
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:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"4096"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
}
...
...
vllm/model_executor/layers/quantization/utils/configs/N=24576,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
{
"1"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_N"
:
25
6
,
"BLOCK_SIZE_M"
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1
6
,
"BLOCK_SIZE_N"
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6
4
,
"BLOCK_SIZE_K"
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128
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1
,
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8
,
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4
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:
{
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6
4
,
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256
,
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1
6
,
"BLOCK_SIZE_N"
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128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
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6
4
,
"num_warps"
:
8
,
"GROUP_SIZE_M"
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1
6
,
"num_warps"
:
4
,
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4
},
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{
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6
4
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_M"
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1
6
,
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64
,
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128
,
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1
6
,
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1
,
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4
,
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3
"num_stages"
:
4
},
"8"
:
{
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:
6
4
,
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128
,
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1
6
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64
,
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128
,
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:
32
,
"GROUP_SIZE_M"
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1
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
5
},
"16"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"24"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
6
4
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"32"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"48"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"64"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"96"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"128"
:
{
"BLOCK_SIZE_M"
:
64
,
...
...
@@ -91,7 +91,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -99,9 +99,9 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
6
4
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"1024"
:
{
"BLOCK_SIZE_M"
:
64
,
...
...
@@ -115,7 +115,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
6
4
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -139,8 +139,8 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
6
4
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
}
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=32768,K=512,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
{
"1"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
8
,
"num_stages"
:
4
"num_stages"
:
3
},
"2"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
6
4
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
8
,
"num_stages"
:
4
"num_stages"
:
3
},
"4"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
8
,
"num_stages"
:
3
"num_stages"
:
4
},
"8"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
...
...
@@ -32,19 +32,19 @@
"num_stages"
:
3
},
"16"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
6
4
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
2
},
"24"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_warps"
:
8
,
"num_stages"
:
3
},
"32"
:
{
...
...
@@ -59,9 +59,9 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"64"
:
{
"BLOCK_SIZE_M"
:
64
,
...
...
@@ -75,7 +75,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -83,7 +83,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -91,7 +91,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
6
4
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -123,7 +123,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -139,7 +139,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
}
...
...
vllm/model_executor/layers/quantization/utils/configs/N=32768,K=512,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
{
"1"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
8
,
"num_stages"
:
4
},
"2"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
8
,
"num_stages"
:
4
"num_stages"
:
3
},
"4"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
128
,
"BLOCK_SIZE_K"
:
64
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
8
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"8"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
2
},
"16"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"BLOCK_SIZE_K"
:
64
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
5
},
"24"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
8
,
"num_stages"
:
3
},
"32"
:
{
...
...
@@ -59,15 +59,15 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
2
},
"64"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -75,7 +75,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -91,7 +91,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -139,7 +139,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
}
...
...
vllm/model_executor/layers/quantization/utils/configs/N=36864,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
{
"1"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
:
5
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
8
,
"num_stages"
:
3
},
"2"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
5
"num_stages"
:
3
},
"4"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
6
4
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"8"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
5
"num_stages"
:
3
},
"16"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"24"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_M"
:
32
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"32"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_M"
:
32
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
...
...
@@ -59,31 +59,31 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"64"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
16
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"96"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
6
4
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"GROUP_SIZE_M"
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1
6
,
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4
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3
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4
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"128"
:
{
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64
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64
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128
,
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4
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"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
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3
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...
...
@@ -99,7 +99,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
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6
4
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
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4
,
"num_stages"
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3
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...
...
@@ -107,7 +107,7 @@
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:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
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4
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"GROUP_SIZE_M"
:
1
6
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"num_warps"
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4
,
"num_stages"
:
3
},
...
...
@@ -123,7 +123,7 @@
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:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
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"GROUP_SIZE_M"
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32
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4
,
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3
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...
...
@@ -131,7 +131,7 @@
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:
64
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"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
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...
...
vllm/model_executor/layers/quantization/utils/configs/N=36864,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
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6
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...
...
@@ -59,33 +59,33 @@
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64
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64
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{
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,
...
...
@@ -93,23 +93,23 @@
"BLOCK_SIZE_K"
:
128
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"GROUP_SIZE_M"
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32
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4
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...
...
@@ -133,7 +133,7 @@
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64
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{
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...
...
vllm/model_executor/layers/quantization/utils/configs/N=4096,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
0 → 100644
View file @
a781e84e
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vllm/model_executor/layers/quantization/utils/configs/N=4096,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
0 → 100644
View file @
a781e84e
{
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vllm/model_executor/layers/quantization/utils/configs/N=576,K=7168,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
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...
...
@@ -8,55 +8,55 @@
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{
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{
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6
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32
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64
,
...
...
@@ -64,74 +64,74 @@
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4
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{
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4
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3
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{
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128
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{
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128
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64
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4
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{
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32
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1
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4
,
"num_stages"
:
3
},
...
...
@@ -139,8 +139,8 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
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1
6
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"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
}
}
vllm/model_executor/layers/quantization/utils/configs/N=576,K=7168,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
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6
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{
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1
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...
...
@@ -80,58 +80,58 @@
"num_stages"
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5
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4
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4
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{
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4
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6
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3
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"1536"
:
{
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:
64
,
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64
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128
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4
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5
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4
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:
{
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:
64
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64
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128
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64
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32
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4
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3
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{
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64
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"GROUP_SIZE_M"
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1
,
"num_warps"
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4
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:
3
},
...
...
@@ -139,7 +139,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
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16
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32
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"num_warps"
:
4
,
"num_stages"
:
3
}
...
...
vllm/model_executor/layers/quantization/utils/configs/N=7168,K=16384,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
{
"1"
:
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:
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128
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"GROUP_SIZE_M"
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64
,
...
...
@@ -16,26 +16,26 @@
"num_stages"
:
5
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"4"
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{
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4
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64
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1
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4
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6
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"16"
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{
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1
6
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4
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"num_stages"
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5
},
...
...
@@ -43,9 +43,9 @@
"BLOCK_SIZE_M"
:
64
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"BLOCK_SIZE_N"
:
64
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:
128
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5
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4
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"32"
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{
"BLOCK_SIZE_M"
:
64
,
...
...
@@ -59,7 +59,7 @@
"BLOCK_SIZE_M"
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64
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64
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32
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4
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"num_stages"
:
4
},
...
...
@@ -67,31 +67,31 @@
"BLOCK_SIZE_M"
:
64
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"BLOCK_SIZE_N"
:
64
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"BLOCK_SIZE_K"
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1
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6
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{
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64
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4
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{
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64
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64
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1
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64
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4
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5
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4
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:
{
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64
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128
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"BLOCK_SIZE_K"
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128
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1
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"GROUP_SIZE_M"
:
32
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"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -101,31 +101,31 @@
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
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4
,
"num_stages"
:
3
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:
4
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"1024"
:
{
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64
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64
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128
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128
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64
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32
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4
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3
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"1536"
:
{
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64
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64
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128
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128
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64
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"num_warps"
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4
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3
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4
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:
{
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64
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128
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"BLOCK_SIZE_K"
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128
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"GROUP_SIZE_M"
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32
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"GROUP_SIZE_M"
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64
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"num_warps"
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4
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"num_stages"
:
3
"num_stages"
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4
},
"3072"
:
{
"BLOCK_SIZE_M"
:
64
,
...
...
@@ -133,7 +133,7 @@
"BLOCK_SIZE_K"
:
128
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"GROUP_SIZE_M"
:
64
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"num_warps"
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4
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"num_stages"
:
3
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4
},
"4096"
:
{
"BLOCK_SIZE_M"
:
64
,
...
...
@@ -141,6 +141,6 @@
"BLOCK_SIZE_K"
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128
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"GROUP_SIZE_M"
:
16
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"num_warps"
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4
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"num_stages"
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3
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:
4
}
}
vllm/model_executor/layers/quantization/utils/configs/N=7168,K=16384,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
{
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...
...
@@ -24,18 +24,18 @@
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...
...
@@ -45,47 +45,47 @@
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64
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"256"
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{
"BLOCK_SIZE_M"
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64
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...
...
@@ -93,29 +93,29 @@
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128
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16
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16
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4
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3
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...
...
@@ -123,7 +123,7 @@
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64
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128
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128
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64
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4
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3
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...
...
@@ -133,7 +133,7 @@
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128
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"GROUP_SIZE_M"
:
32
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4
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{
"BLOCK_SIZE_M"
:
64
,
...
...
vllm/model_executor/layers/quantization/utils/configs/N=7168,K=18432,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
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"24"
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{
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64
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...
...
@@ -45,7 +45,7 @@
"BLOCK_SIZE_K"
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128
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1
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4
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5
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4
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"32"
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{
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64
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...
...
@@ -59,7 +59,7 @@
"BLOCK_SIZE_M"
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64
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64
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1
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64
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4
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"num_stages"
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5
},
...
...
@@ -73,19 +73,19 @@
},
"96"
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{
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64
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"256"
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{
"BLOCK_SIZE_M"
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64
,
...
...
@@ -99,21 +99,21 @@
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64
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128
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128
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64
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...
...
@@ -123,9 +123,9 @@
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64
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:
128
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128
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"3072"
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{
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64
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...
...
@@ -133,7 +133,7 @@
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128
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32
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4
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3
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4
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"4096"
:
{
"BLOCK_SIZE_M"
:
64
,
...
...
vllm/model_executor/layers/quantization/utils/configs/N=7168,K=18432,device_name=NVIDIA_H200,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
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"64"
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{
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64
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...
...
@@ -73,25 +73,25 @@
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{
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64
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32
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16
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4
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3
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...
...
@@ -99,31 +99,31 @@
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64
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128
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"BLOCK_SIZE_K"
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128
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32
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64
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4
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3
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4
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{
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64
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128
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128
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32
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4
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3
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4
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{
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64
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64
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128
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128
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6
4
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1
6
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4
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3
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4
},
"2048"
:
{
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64
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"BLOCK_SIZE_N"
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128
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"BLOCK_SIZE_K"
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128
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6
4
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"GROUP_SIZE_M"
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1
6
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"num_warps"
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4
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"num_stages"
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3
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...
...
@@ -133,7 +133,7 @@
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16
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"4096"
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{
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64
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...
...
@@ -141,6 +141,6 @@
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128
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32
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4
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"num_stages"
:
3
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4
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}
vllm/model_executor/layers/quantization/utils/configs/N=7168,K=2048,device_name=NVIDIA_H100_80GB_HBM3,dtype=fp8_w8a8,block_shape=[128,128].json
View file @
a781e84e
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128
,
"GROUP_SIZE_M"
:
16
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
5
"num_stages"
:
3
},
"4"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
:
5
"num_stages"
:
3
},
"8"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
6
4
,
"num_warps"
:
4
,
"num_stages"
:
5
"num_stages"
:
3
},
"16"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"24"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
6
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"32"
:
{
"BLOCK_SIZE_M"
:
6
4
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_M"
:
1
6
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
4
},
...
...
@@ -59,39 +59,39 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
4
"num_stages"
:
3
},
"64"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"96"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
4
},
"128"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"GROUP_SIZE_M"
:
1
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"256"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
6
4
,
"GROUP_SIZE_M"
:
1
6
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -99,23 +99,23 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
16
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
},
"1024"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
},
"1536"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -123,7 +123,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -131,7 +131,7 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
1
,
"GROUP_SIZE_M"
:
64
,
"num_warps"
:
4
,
"num_stages"
:
3
},
...
...
@@ -139,8 +139,8 @@
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
64
,
"GROUP_SIZE_M"
:
32
,
"num_warps"
:
4
,
"num_stages"
:
3
"num_stages"
:
4
}
}
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mgoin <mgoin64@gmail.com>mgoin <mgoin64@gmail.com>