Benchmarks

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.