Benchmark

ARM CPU

Note: If a board has big.LITTLE architecture, we will use all big cores. Otherwise, we will use all cores. In the following device specifications, we only list the cores being used.

• Firefly-RK3399 : 2 x Cortex A73 1.8Ghz

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Network Name         Mean Inference Time (std dev)
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squeezenet v1.1      48.87 ms            (1.07 ms)
mobilenet            82.16 ms            (0.09 ms)
resnet-18            162.55 ms           (0.14 ms)
vgg-16               912.44 ms           (0.32 ms)

• Raspberry Pi 3B : 4 x Cortex A53 1.2Ghz

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Network Name         Mean Inference Time (std dev)
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squeezenet v1.1      92.34 ms            (0.07 ms)
mobilenet            145.22 ms           (0.11 ms)
resnet-18            325.06 ms           (0.23 ms)
vgg-16               crashed due to out of memeory

• Huawei P20 Pro / Mate10 Pro (Soc: HiSilicon Kirin 970) : (4 x Cortex A73 2.36GHz)

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Network Name         Mean Inference Time (std dev)
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squeezenet v1.1      27.53 ms            (1.14 ms)
mobilenet            46.53 ms            (0.31 ms)
resnet-18            76.74 ms            (0.18 ms)
vgg-16               479.84 ms           (0.92 ms)

• Google Pixel 2 (Soc: Qualcomm Snapdragon 835) : (4 × Kyro 2.35 GHz)

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Network Name         Mean Inference Time (std dev)
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squeezenet v1.1      23.57 ms            (0.42 ms)
mobilenet            40.73 ms            (0.11 ms)
resnet-18            63.95 ms            (0.03 ms)
vgg-16               407.75 ms           (9.57 ms)

• PYNQ (2 x Cortex-A9 650MHz)

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Network Name         Mean Inference Time (std dev)
--------------------------------------------------
squeezenet v1.1      452.40 ms           (0.09 ms)
mobilenet            772.16 ms           (0.25 ms)
resnet-18            1243.49 ms          (0.67 ms)
vgg-16               crashed due to out of memeory

Reproduce

see readme page here https://github.com/dmlc/tvm/tree/master/apps/benchmark on how to get these numbers