未验证 提交 8bbba49b 编写于 作者: J juncaipeng 提交者: GitHub

update benchmark data (#2335)

* update benchmark results, test=develop
上级 1da984ab
......@@ -46,27 +46,28 @@ title: Benchmark 数据
* HUAWEI Mate10
* 测试说明
* commit id: 12c129affaacd476e27a0a82b235a9d547d33f0f
* branch: release/2.0.0
* warmup=10, repeats=30,统计平均时间,单位是ms
* 当线程数为1时,```DeviceInfo::Global().SetRunMode```设置LITE_POWER_HIGH,否者设置LITE_POWER_NO_BIND
* 模型的输入图像的维度是{1, 3, 224, 224},输入图像的每一位数值是1
# 测试数据
## fp32 模型测试数据
## fp32模型测试数据
### paddlepaddle model
骁龙855|armv8 | | |armv7 | | |
骁龙855|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----
threads num|1 |2 |4 |1 |2 |4
mobilenet_v1 |32.19 |18.81 |10.90 |30.92 |18.31 |10.15
mobilenet_v2 |22.91 |13.75 |8.64 |21.15 |12.79 |7.84
shufflenet_v2 |4.67 |3.37 |2.65 |4.43 |3.15 |2.66
squeezenet_v1.1 |25.10 |15.93 |9.68 |23.28 |14.61 |8.71
mnasnet |21.84 |13.14 |7.96 |23.29 |12.46 |7.48
mnasnet |21.84 |13.14 |7.96 |19.61 |11.88 |7.55
骁龙835|armv8 | | |armv7 | | |
骁龙835|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----
threads num|1 |2 |4 |1 |2 |4
mobilenet_v1 |94.13 |52.17 |30.68 |88.28 |47.58 |26.64
......@@ -75,7 +76,8 @@ shufflenet_v2 |10.87 |6.92 |5.12 |10.41 |6.76 |4.97
squeezenet_v1.1 |73.61 |42.25 |24.44 |64.87 |38.43 |23.06
mnasnet |58.22 |33.43 |20.44 |53.43 |30.20 |18.09
麒麟980|armv8 | | |armv7 | | |
麒麟980|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----
threads num|1 |2 |4 |1 |2 |4
mobilenet_v1 |55.11 |28.24 |13.27 |34.24 |17.74 |12.41
......@@ -84,7 +86,7 @@ shufflenet_v2 |7.26 |4.94 |15.06 |5.32 |3.33 |2.82
squeezenet_v1.1 |42.73 |23.66 |57.39 |26.03 |14.53 |13.66
mnasnet |36.87 |20.15 |46.04 |21.85 |12.06 |8.68
麒麟970|armv8 | | |armv7 | | |
麒麟970|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----
threads num|1 |2 |4 |1 |2 |4
mobilenet_v1 |97.80 |52.64 |34.46 |94.51 |49.36 |28.43
......@@ -95,52 +97,54 @@ mnasnet |61.86 |34.62 |22.68 |59.61 |32.79 |19.56
## caffe model
骁龙855|armv8 | | |armv7 | | |
骁龙855|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----|
threads num|1 |2 |4 |1 |2 |4 |
mobilenet_v1 |32.42 |18.68 |10.86 |30.92 |18.35 |10.07 |
mobilenet_v2 |29.53 |17.76 |10.89 |27.19 |16.53 |9.75 |
shufflenet_v2 |4.61 |3.29 |2.61 |4.36 |3.11 |2.51 |
骁龙835|armv8 | | |armv7 | | |
骁龙835|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----|
threads num|1 |2 |4 |1 |2 |4 |
mobilenet_v1 |92.52 |52.34 |30.37 |88.31 |49.75 |27.29 |
mobilenet_v2 |79.50 |45.67 |28.79 |76.13 |44.01 |26.13 |
shufflenet_v2 |10.94 |7.08 |5.16 |10.64 |6.83 |5.01 |
麒麟980|armv8 | | |armv7 | | |
麒麟980|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----|
threads num|1 |2 |4 |1 |2 |4 |
mobilenet_v1 |55.36 |28.18 |13.31 |34.42 |17.93 |12.52 |
mobilenet_v2 |49.17 |26.10 |65.49 |30.50 |16.66 |11.72 |
shufflenet_v2 |8.45 |5.00 |15.65 |4.58 |3.14 |2.83 |
麒麟970|armv8 | | |armv7 | | |
麒麟970|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----|
threads num|1 |2 |4 |1 |2 |4 |
mobilenet_v1 |97.85 |53.38 |33.85 |94.29 |49.42 |28.29 |
mobilenet_v2 |87.40 |50.25 |31.85 |85.55 |48.11 |28.24 |
shufflenet_v2 |12.16 |8.39 |6.21 |12.21 |8.33 |6.32 |
## 量化模型
## int8量化模型测试数据
骁龙855|armv8 | | |armv7 | | |
骁龙855|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----|
threads num|1 |2 |4 |1 |2 |4 |
mobilenet_v1 |14.01 |8.13 |4.32 |36.80 |21.58 |11.12 |
mobilenet_v2 |17.24 |11.55 |7.82 |28.72 |19.08 |12.49 |
mobilenet_v1 |36.80 |21.58 |11.12 | 14.01 |8.13 |4.32 |
mobilenet_v2 |28.72 |19.08 |12.49 | 17.24 |11.55 |7.82 |
骁龙835|armv8 | | |armv7 | | |
骁龙835|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----|
threads num|1 |2 |4 |1 |2 |4 |
mobilenet_v1 |56.57 |29.84 |15.24 |60.76 |32.25 |16.66 |
mobilenet_v2 |47.52 |28.18 |19.24 |49.38 |31.10 |22.07 |
mobilenet_v1 |60.76 |32.25 |16.66 |56.57 |29.84 |15.24 |
mobilenet_v2 |49.38 |31.10 |22.07 |47.52 |28.18 |19.24 |
骁龙970|armv8 | | |armv7 | | |
骁龙970|armv7 | | |armv8 | | |
----| ---- | ---- | ---- | ---- |---- |----|
threads num|1 |2 |4 |1 |2 |4 |
mobilenet_v1 |60.86 |30.98 |16.31 |65.95 |34.39 |18.68 |
mobilenet_v2 |65.57 |37.31 |20.87 |68.87 |39.39 |24.43 |
mobilenet_v1 |65.95 |34.39 |18.68 |60.86 |30.98 |16.31 |
mobilenet_v2 |68.87 |39.39 |24.43 |65.57 |37.31 |20.87 |
\ No newline at end of file
......@@ -3,7 +3,7 @@ layout: post
title: Paddle-Lite文档
---
> 版本:develop
> 版本:v2.0.0
Paddle-Lite 框架是 PaddleMobile 新一代架构,重点支持移动端推理预测,特点**高性能、多硬件、轻量级** 。支持PaddleFluid/TensorFlow/Caffe/ONNX模型的推理部署,目前已经支持 ARM CPU, Mali GPU, Adreno GPU, Huawei NPU 等多种硬件,正在逐步增加 X86 CPU, Nvidia GPU 等多款硬件,相关硬件性能业内领先。
......
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