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Update performance data on Raspberry Pi
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@Maratyszcza @xnnpack-bot
Maratyszcza authored and xnnpack-bot committed Oct 15, 2021
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Expand Up @@ -56,36 +56,38 @@ All operators in XNNPACK support NHWC layout, but additionally allow custom stri

The table below presents **single-threaded** performance of XNNPACK library on three generations of MobileNet models and three generations of Pixel phones.

| Model | Pixel, ms | Pixel 2, ms | Pixel 3a, ms |
| ------------------ | :-------: | :---------: | :----------: |
| MobileNet v1 1.0X | 82 | 86 | 88 |
| MobileNet v2 1.0X | 49 | 53 | 55 |
| MobileNet v3 Large | 39 | 42 | 44 |
| MobileNet v3 Small | 12 | 14 | 14 |
| Model | Pixel, ms | Pixel 2, ms | Pixel 3a, ms |
| ----------------------- | :-------: | :---------: | :----------: |
| FP32 MobileNet v1 1.0X | 82 | 86 | 88 |
| FP32 MobileNet v2 1.0X | 49 | 53 | 55 |
| FP32 MobileNet v3 Large | 39 | 42 | 44 |
| FP32 MobileNet v3 Small | 12 | 14 | 14 |

The following table presents **multi-threaded** (using as many threads as there are big cores) performance of XNNPACK library on three generations of MobileNet models and three generations of Pixel phones.

| Model | Pixel, ms | Pixel 2, ms | Pixel 3a, ms |
| ------------------ | :-------: | :---------: | :----------: |
| MobileNet v1 1.0X | 43 | 27 | 46 |
| MobileNet v2 1.0X | 26 | 18 | 28 |
| MobileNet v3 Large | 22 | 16 | 24 |
| MobileNet v3 Small | 7 | 6 | 8 |
| Model | Pixel, ms | Pixel 2, ms | Pixel 3a, ms |
| ----------------------- | :-------: | :---------: | :----------: |
| FP32 MobileNet v1 1.0X | 43 | 27 | 46 |
| FP32 MobileNet v2 1.0X | 26 | 18 | 28 |
| FP32 MobileNet v3 Large | 22 | 16 | 24 |
| FP32 MobileNet v3 Small | 7 | 6 | 8 |

Benchmarked on March 27, 2020 with `end2end_bench --benchmark_min_time=5` on an Android/ARM64 build with Android NDK r21 (`bazel build -c opt --config android_arm64 :end2end_bench`) and neural network models with randomized weights and inputs.

### Raspberry Pi

The table below presents **multi-threaded** performance of XNNPACK library on three generations of MobileNet models and three generations of Raspberry Pi boards.

| Model | RPi Zero W (BCM2835), ms | RPi 2 (BCM2836), ms | RPi 3+ (BCM2837B0), ms | RPi 4 (BCM2711), ms |
| ------------------ | :----------------------: | :-----------------: | :--------------------: | :-----------------: |
| MobileNet v1 1.0X | 4004 | 337 | 116 | 72 |
| MobileNet v2 1.0X | 2011 | 195 | 83 | 41 |
| MobileNet v3 Large | 1694 | 163 | 70 | 38 |
| MobileNet v3 Small | 482 | 52 | 23 | 13 |
| Model | RPi Zero W (BCM2835), ms | RPi 2 (BCM2836), ms | RPi 3+ (BCM2837B0), ms | RPi 4 (BCM2711), ms | RPi 4 (BCM2711, ARM64), ms |
| ----------------------- | :----------------------: | :-----------------: | :--------------------: | :-----------------: | :------------------------: |
| FP32 MobileNet v1 1.0X | 3937 | 299 | 114 | 72 | 76 |
| FP32 MobileNet v2 1.0X | 1987 | 187 | 79 | 41 | 44 |
| FP32 MobileNet v3 Large | 1658 | 158 | 67 | 38 | 41 |
| FP32 MobileNet v3 Small | 487 | 50 | 23 | 13 | 14 |
| INT8 MobileNet v1 1.0X | 2598 | 169 | 61 | 29 | 24 |
| INT8 MobileNet v2 1.0X | 1487 | 109 | 40 | 20 | 17 |

Benchmarked on May 22, 2020 with `end2end-bench --benchmark_min_time=5` on a Raspbian Buster build with CMake (`./scripts/build-local.sh`) and neural network models with randomized weights and inputs.
Benchmarked on Oct 15, 2021 with `end2end-bench --benchmark_min_time=5` on a Raspbian Buster build with CMake (`./scripts/build-local.sh`) and neural network models with randomized weights and inputs. INT8 inference was evaluated on per-channel quantization schema.

## Publications

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