Mobile Neural Network 1.0.0

pts/mnn-1.0.0 - 17 September 2020 - Initial commit of Alibaba MNN deep learning framework benchmark.

downloads.xml

<?xml version="1.0"?>
<!--Phoronix Test Suite v10.0.0m2-->
<PhoronixTestSuite>
  <Downloads>
    <Package>
      <URL>http://www.phoronix-test-suite.com/benchmark-files/MNN-20200917.tar.xz</URL>
      <MD5>3ff6ec706704f5f83c6e4766e40491f6</MD5>
      <SHA256>547724ab279f2b1a8f83e64d327be7cd17b9ddda17636c64d5a0cdfb9a7ee118</SHA256>
      <FileName>MNN-20200917.tar.xz</FileName>
      <FileSize>4831952</FileSize>
    </Package>
  </Downloads>
</PhoronixTestSuite>

install.sh

#!/bin/sh

tar -xf MNN-20200917.tar.xz
rm -rf MNN-master
mv MNN MNN-master
cd MNN-master
cd schema
./generate.sh
cd ..
mkdir build
cd build
cmake .. -DMNN_BUILD_BENCHMARK=true 
make -j $NUM_CPU_CORES
echo $? > ~/install-exit-status

cd ~/
cat>mnn<<EOT
#!/bin/sh
cd MNN-master/build
./benchmark.out ../benchmark/models/ 1000 100 0 \$NUM_CPU_CORES > \$LOG_FILE
echo \$? > ~/test-exit-status
EOT
chmod +x mnn

results-definition.xml

<?xml version="1.0"?>
<!--Phoronix Test Suite v10.0.0m2-->
<PhoronixTestSuite>
  <ResultsParser>
    <OutputTemplate>[ - ] SqueezeNetV1.0.mnn          max =    6.784ms  min =    6.030ms  avg =    #_RESULT_#</OutputTemplate>
    <LineHint>SqueezeNetV1.0.mnn</LineHint>
    <StripFromResult>ms</StripFromResult>
    <ArgumentsDescription>Model: SqueezeNetV1.0</ArgumentsDescription>
  </ResultsParser>
  <ResultsParser>
    <OutputTemplate>[ - ] resnet-v2-50.mnn          max =    6.784ms  min =    6.030ms  avg =    #_RESULT_#</OutputTemplate>
    <LineHint>resnet-v2-50.mnn</LineHint>
    <StripFromResult>ms</StripFromResult>
    <ArgumentsDescription>Model: resnet-v2-50</ArgumentsDescription>
  </ResultsParser>
  <ResultsParser>
    <OutputTemplate>[ - ] MobileNetV2_224.mnn          max =    6.784ms  min =    6.030ms  avg =    #_RESULT_#</OutputTemplate>
    <LineHint>MobileNetV2_224.mnn</LineHint>
    <StripFromResult>ms</StripFromResult>
    <ArgumentsDescription>Model: MobileNetV2_224</ArgumentsDescription>
  </ResultsParser>
  <ResultsParser>
    <OutputTemplate>[ - ] mobilenet-v1-1.0.mnn          max =    6.784ms  min =    6.030ms  avg =    #_RESULT_#</OutputTemplate>
    <LineHint>mobilenet-v1-1.0.mnn</LineHint>
    <StripFromResult>ms</StripFromResult>
    <ArgumentsDescription>Model: mobilenet-v1-1.0</ArgumentsDescription>
  </ResultsParser>
  <ResultsParser>
    <OutputTemplate>[ - ] inception-v3.mnn          max =    6.784ms  min =    6.030ms  avg =    #_RESULT_#</OutputTemplate>
    <LineHint>inception-v3.mnn</LineHint>
    <StripFromResult>ms</StripFromResult>
    <ArgumentsDescription>Model: inception-v3</ArgumentsDescription>
  </ResultsParser>
</PhoronixTestSuite>

test-definition.xml

<?xml version="1.0"?>
<!--Phoronix Test Suite v10.0.0m2-->
<PhoronixTestSuite>
  <TestInformation>
    <Title>Mobile Neural Network</Title>
    <AppVersion>2020-09-17</AppVersion>
    <Description>MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by ALibaba.</Description>
    <ResultScale>ms</ResultScale>
    <Proportion>LIB</Proportion>
    <TimesToRun>3</TimesToRun>
  </TestInformation>
  <TestProfile>
    <Version>1.0.0</Version>
    <SupportedPlatforms>Linux</SupportedPlatforms>
    <SoftwareType>Scientific</SoftwareType>
    <TestType>System</TestType>
    <License>Free</License>
    <Status>Verified</Status>
    <ExternalDependencies>cmake, build-utilities</ExternalDependencies>
    <EnvironmentSize>2700</EnvironmentSize>
    <ProjectURL>https://github.com/alibaba/MNN</ProjectURL>
    <Maintainer>Michael Larabel</Maintainer>
  </TestProfile>
</PhoronixTestSuite>