Benchmarks

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This document describes the MindSpore benchmarks. For details about the MindSpore pre-trained model, see Model Zoo.

Training Performance

ResNet

Network

Network Type

Dataset

MindSpore Version

Resource                

Precision

Batch Size

Throughput

Speedup

ResNet-50 v1.5

CNN

ImageNet2012

0.2.0-alpha

Ascend: 1 * Ascend 910
CPU:24 Cores

Mixed

32

1787 images/sec

-

Ascend: 8 * Ascend 910
CPU:192 Cores

Mixed

32

13689 images/sec

0.95

Ascend: 16 * Ascend 910
CPU:384 Cores

Mixed

32

27090 images/sec

0.94

  1. The preceding performance is obtained based on ModelArts, the HUAWEI CLOUD AI development platform. It is the average performance obtained by the Ascend 910 AI processor during the overall training process.

  2. For details about other open source frameworks, see ResNet-50 v1.5 for TensorFlow.

BERT

Network

Network Type

Dataset

MindSpore Version

Resource                

Precision

Batch Size

Throughput

Speedup

BERT-Large

Attention

zhwiki

0.2.0-alpha

Ascend: 1 * Ascend 910
CPU:24 Cores

Mixed

96

210 sentences/sec

-

Ascend: 8 * Ascend 910
CPU:192 Cores

Mixed

96

1613 sentences/sec

0.96

  1. The preceding performance is obtained based on ModelArts, the HUAWEI CLOUD AI development platform. The network contains 24 hidden layers, the sequence length is 128 tokens, and the vocabulary contains 21128 tokens.

  2. For details about other open source frameworks, see BERT For TensorFlow.