mirror of
https://github.com/deepinsight/insightface.git
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54 lines
3.1 KiB
Markdown
54 lines
3.1 KiB
Markdown
# Training performance report on NVIDIA A100
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[NVIDIA A100 Tensor Core GPU](https://www.nvidia.com/en-us/data-center/a100/)
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## Test Server Spec
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| Key | Value |
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| ------------ | ------------------------------------------------ |
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| System | ServMax G408-X2 Rackmountable Server |
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| CPU | 2 x Intel(R) Xeon(R) Gold 5220R CPU @ 2.20GHz |
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| Memory | 384GB, 12 x Samsung 32GB DDR4-2933 |
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| GPU | 8 x NVIDIA A100 80GB |
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| Cooling | 2x Customized GPU Kit for GPU support FAN-1909L2 |
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| Hard Drive | Intel SSD S4500 1.9TB/SATA/TLC/2.5" |
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| OS | Ubuntu 16.04.7 LTS |
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| Installation | CUDA 11.1, cuDNN 8.0.5 |
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| Installation | Python 3.7.10 |
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| Installation | PyTorch 1.9.0 (conda) |
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This server is donated by [AMAX](https://www.amaxchina.com/), many thanks!
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## Experiments on arcface_torch
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We report training speed in following table, please also note that:
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1. The training dataset is in mxnet record format and located on SSD hard drive.
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2. Embedding-size are all set to 512.
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3. We use large datasets with about 618K/2M identities to simulate real cases.
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4. We test the 10K batch-size on real dataset to take the full advantage of 80GB memory.
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5. We also test on huge synthetic datasets which include 50M~80M classes.
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| Dataset | Classes | Backbone | Batch-size | PFC | FP16 | TF32 | Samples/sec | GPU Mem(GB) |
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| ----------- | ------- | ----------- | ---------- | ---- | ---- | ---- | ----------- | ----------- |
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| WebFace600K | 618K | IResNet-50 | 1024 | × | × | × | ~3670 | ~18.2 |
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| WebFace600K | 618K | IResNet-50 | 1024 | × | × | √ | ~4760 | ~15.0 |
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| WebFace600K | 618K | IResNet-50 | 1024 | × | √ | × | ~5170 | ~10.1 |
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| WebFace600K | 618K | IResNet-50 | 1024 | × | √ | √ | ~5400 | ~10.1 |
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| WebFace600K | 618K | IResNet-50 | 2048 | × | √ | √ | ~7780 | ~16.4 |
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| WebFace600K | 618K | IResNet-50 | 10240 | × | √ | √ | ~9400 | ~66.7 |
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| WebFace600K | 618K | IResNet-100 | 1024 | × | √ | √ | ~3700 | ~13.1 |
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| WebFace600K | 618K | IResNet-180 | 1024 | × | √ | √ | ~2380 | ~17.5 |
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| WebFace2M | 2M | IResNet-100 | 1024 | × | √ | √ | ~3480 | ~20.5 |
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| WebFace2M | 2M | IResNet-180 | 1024 | × | √ | √ | ~2350 | ~25.0 |
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| WebFace2M | 2M | IResNet-300 | 1024 | × | √ | √ | ~1541 | ~32.6 |
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| Virtual | 50M | IResNet-50 | 1024 | 0.1 | √ | √ | ~2700 | ~54.1 |
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| Virtual | 70M | IResNet-50 | 1024 | 0.1 | √ | √ | ~2170 | ~73.7 |
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| Virtual | 80M | IResNet-50 | 1024 | 0.1 | √ | √ | ~1080 | ~79.6 |
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