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8 years ago | |
|---|---|---|
| .. | ||
| CMakeLists.txt | 8 years ago | |
| README.md | 8 years ago | |
| alexnet.param | 8 years ago | |
| benchncnn.cpp | 8 years ago | |
| googlenet.param | 8 years ago | |
| mobilenet.param | 8 years ago | |
| mobilenet_ssd.param | 8 years ago | |
| mobilenet_v2.param | 8 years ago | |
| resnet18.param | 8 years ago | |
| shufflenet.param | 8 years ago | |
| squeezenet.param | 8 years ago | |
| squeezenet_ssd.param | 8 years ago | |
| vgg16.param | 8 years ago | |
benchncnn can be used to test neural network inference performance
Only the network definition files (ncnn param) are required.
The large model binary files (ncnn bin) are not loaded but generated randomly for speed test.
More model networks may be added later.
Usage
# copy all param files to the current directory
./benchncnn [loop count] [num threads] [powersave]
Typical output (executed in android adb shell)
HM2014812:/data/local/tmp # ./benchncnn 8 4 0
loop_count = 8
num_threads = 4
powersave = 0
squeezenet min = 98.27 max = 118.75 avg = 105.22
mobilenet min = 168.36 max = 178.58 avg = 174.52
mobilenet_v2 min = 192.38 max = 210.21 avg = 201.79
shufflenet min = 66.07 max = 74.64 avg = 70.58
googlenet min = 327.53 max = 344.18 avg = 334.36
resnet18 min = 465.24 max = 479.58 avg = 470.86
alexnet min = 380.57 max = 406.64 avg = 397.66
vgg16 min = 2341.65 max = 2475.65 avg = 2402.14
squeezenet-ssd min = 187.64 max = 283.71 avg = 204.29
mobilenet-ssd min = 183.96 max = 214.15 avg = 193.30
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