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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/05/01 07:01:07 UTC
[GitHub] zheng-da commented on a change in pull request #10761: update the
performance page of MXNet.
zheng-da commented on a change in pull request #10761: update the performance page of MXNet.
URL: https://github.com/apache/incubator-mxnet/pull/10761#discussion_r185176560
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File path: docs/faq/perf.md
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@@ -101,88 +106,90 @@ We suggest always checking to make sure that a recent cuDNN version is used.
Setting the environment `export MXNET_CUDNN_AUTOTUNE_DEFAULT=1` sometimes also helps.
-We show results when using various GPUs including K80 (EC2 p2.2xlarge), M40,
-and P100 (DGX-1).
+We show results when using various GPUs including K80 (EC2 p2.2xlarge), M60 (EC2 g3.4xlarge),
+and V100 (EC2 p3.2xlarge).
### Scoring results
Based on
[example/image-classification/benchmark_score.py](https://github.com/dmlc/mxnet/blob/master/example/image-classification/benchmark_score.py)
-and MXNet commit `0a03417`, with cuDNN 5.1
+and [MXNet-1.2.0.rc1](https://github.com/apache/incubator-mxnet/releases/download/1.2.0.rc1/apache-mxnet-src-1.2.0.rc1-incubating.tar.gz), with cuDNN 7.0.5
- K80 (single GPU)
- | Batch | Alexnet | VGG | Inception-BN | Inception-v3 | Resnet 50 | Resnet 152 |
- | --- | --- | --- | --- | --- | --- | --- |
- | 1 | 202.66 | 70.76 | 74.91 | 42.61 | 70.94 | 24.87 |
- | 2 | 233.76 | 63.53 | 119.60 | 60.09 | 92.28 | 34.23 |
- | 4 | 367.91 | 78.16 | 164.41 | 72.30 | 116.68 | 44.76 |
- | 8 | 624.14 | 119.06 | 195.24 | 79.62 | 129.37 | 50.96 |
- | 16 | 1071.19 | 195.83 | 256.06 | 99.38 | 160.40 | 66.51 |
- | 32 | 1443.90 | 228.96 | 287.93 | 106.43 | 167.12 | 69.73 |
-
-- M40
-
- | Batch | Alexnet | VGG | Inception-BN | Inception-v3 | Resnet 50 | Resnet 152 |
- | --- | --- | --- | --- | --- | --- | --- |
- | 1 | 412.09 | 142.10 | 115.89 | 64.40 | 126.90 | 46.15 |
- | 2 | 743.49 | 212.21 | 205.31 | 108.06 | 202.17 | 75.05 |
- | 4 | 1155.43 | 280.92 | 335.69 | 161.59 | 266.53 | 106.83 |
- | 8 | 1606.87 | 332.76 | 491.12 | 224.22 | 317.20 | 128.67 |
- | 16 | 2070.97 | 400.10 | 618.25 | 251.87 | 335.62 | 134.60 |
- | 32 | 2694.91 | 466.95 | 624.27 | 258.59 | 373.35 | 152.71 |
-
-- P100
-
- | Batch | Alexnet | VGG | Inception-BN | Inception-v3 | Resnet 50 | Resnet 152 |
- | --- | --- | --- | --- | --- | --- | --- |
- | 1 | 624.84 | 294.6 | 139.82 | 80.17 | 162.27 | 58.99 |
- | 2 | 1226.85 | 282.3 | 267.41 | 142.63 | 278.02 | 102.95 |
- | 4 | 1934.97 | 399.3 | 463.38 | 225.56 | 423.63 | 168.91 |
- | 8 | 2900.54 | 522.9 | 709.30 | 319.52 | 529.34 | 210.10 |
- | 16 | 4063.70 | 755.3 | 949.22 | 444.65 | 647.43 | 270.07 |
- | 32 | 4883.77 | 854.4 | 1197.74 | 493.72 | 713.17 | 294.17 |
+| Batch | Alexnet | VGG | Inception-BN | Inception-v3 | Resnet 50 | Resnet 152 |
+|-------|---------|--------|--------------|--------------|-----------|------------|
+| 1 | 243.93 | 43.59 | 68.62 | 35.52 | 67.41 | 23.65 |
Review comment:
First, @mli told me that M60 is supposed to be slower than M40.
VGG is slower because a different model was used. The original performance was measured a long time ago. Since then, the implementation of VGG has changed. The current version of VGG has many more layers. If you want to know more details, I think @TaoLv can tell you more.
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