STM32Cube.AI model performances

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This article is providing benchmark of a set of well-known or reference pre-trained neural network models.

Info white.png Information
  • STM32Cube.AI is a software aiming at the generation of optimized C code for STM32 and neural network inference. It is delivered under the Mix Ultimate Liberty+OSS+3rd-party V1 software license agreement (SLA0048).
  • Inference time, current and energy measures process is described, not done in a certified laboratory but can be reproduce by any user. The results are average values and will vary depending on the input data (random data are currently used), temperature and the STM32 device itself.
  • Published data on this article are not contractual.

1. Benchmark results

2. Measure process

Only the machine learning inference is considered. In a complete application, the sensor acquisition, the data conditioning and pre-processing shall also be considered. The memory footprint are the one reported by X-CUBE-AI using the "Analyze" function (the version of X-CUBE-AI used is mentioned in the table). The input / output buffers are included, but the options have been selected allowing to overlay these buffers with the activations. The input / output buffer size are reported. The inference time as well as the X-Cross error is the one reported by the "Validation on target". When power measure is

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