UL Procyon definition files let you set up and run the benchmark with standard or custom settings. By default, these definition files are found in C:\Program Files\UL\Procyon\. 

ai_computer_vision_openvino.def

Use this definition file to run the UL Procyon AI Computer Vision Benchmark with default settings and using OpenVino. Using this definition file is the same as running the benchmark from the GUI.

<?xml version="1.0" encoding="utf-8"?>
<benchmark>
  <test_info>
    <benchmark_tests>
      <benchmark_test name="AIOpenVinoBenchmark" test_run_type="EXPLICIT" version="1.0"/>
    </benchmark_tests>
  </test_info>
  <application_info>
    <selected_workloads>
      <selected_workload name="AIMobileNetV3Default"/>
	  <selected_workload name="AIInceptionV4Default"/>
	  <selected_workload name="AIResNet50Default"/>
	  <selected_workload name="AIDeepLabV3Default"/>
	  <selected_workload name="AIYOLOV3Default"/>
	  <selected_workload name="AIESRGANDefault"/>
    </selected_workloads>
  </application_info>
  <settings>
    <setting>
      <name>ai_device_type</name>
      <value>CPU</value><!--Options: CPU, GPU, GPU.0, GPU.1 -->
    </setting>
    <setting>
      <name>ai_inference_precision</name>
      <value>float32</value><!--Options: float32, float16, integer -->
    </setting>
  </settings>
</benchmark>

ai_computer_vision_snpe.def

Use this definition file to run the UL Procyon AI Computer Vision Benchmark with default settings and using Qualcomm SNPE. Using this definition file is the same as running the benchmark from the GUI.

<?xml version="1.0" encoding="utf-8"?>
<benchmark>
  <test_info>
    <benchmark_tests>
      <benchmark_test name="AISNPEBenchmark" test_run_type="EXPLICIT" version="1.0"/>
    </benchmark_tests>
  </test_info>
  <application_info>
    <selected_workloads>
      <selected_workload name="AIMobileNetV3Default"/>
	  <selected_workload name="AIInceptionV4Default"/>
	  <selected_workload name="AIResNet50Default"/>
	  <selected_workload name="AIDeepLabV3Default"/>
	  <selected_workload name="AIYOLOV3Default"/>
	  <selected_workload name="AIESRGANDefault"/>
    </selected_workloads>
  </application_info>
  <settings>
    <setting>
        <name>ai_device_type</name>
        <value>HTP</value>
      </setting>
    <setting>
      <name>ai_inference_precision</name>
      <value>integer</value>
    </setting>
  </settings>
</benchmark>


ai_computer_vision_tensorrt.def

Use this definition file to run the UL Procyon AI Computer Vision Benchmark with default settings and using NVIDIA TensorRT. Using this definition file is the same as running the benchmark from the GUI.

<?xml version="1.0" encoding="utf-8"?>
<benchmark>
  <test_info>
    <benchmark_tests>
      <benchmark_test name="AITensorRTBenchmark" test_run_type="EXPLICIT" version="1.0"/>
    </benchmark_tests>
  </test_info>
  <application_info>
    <selected_workloads>
      <selected_workload name="AIMobileNetV3Default"/>
	  <selected_workload name="AIInceptionV4Default"/>
	  <selected_workload name="AIResNet50Default"/>
	  <selected_workload name="AIDeepLabV3Default"/>
	  <selected_workload name="AIYOLOV3Default"/>
	  <selected_workload name="AIESRGANDefault"/>
    </selected_workloads>
  </application_info>
  <settings>
    <setting>
      <name>ai_inference_precision</name>
      <value>float32</value><!--Options: float32, float16, integer -->
    </setting>
  </settings>
</benchmark>


ai_computer_vision_winml.def

Use this definition file to run the UL Procyon AI Computer Vision Benchmark with default settings and using Microsoft Windows ML. Using this definition file is the same as running the benchmark from the GUI.

<?xml version="1.0" encoding="utf-8"?>
<benchmark>
  <test_info>
    <benchmark_tests>
      <benchmark_test name="AIWinMLBenchmark" test_run_type="EXPLICIT" version="1.0"/>
    </benchmark_tests>
  </test_info>
  <application_info>
    <selected_workloads>
      <selected_workload name="AIMobileNetV3Default"/>
	  <selected_workload name="AIInceptionV4Default"/>
	  <selected_workload name="AIResNet50Default"/>
	  <selected_workload name="AIDeepLabV3Default"/>
	  <selected_workload name="AIYOLOV3Default"/>
	  <selected_workload name="AIESRGANDefault"/>
    </selected_workloads>
  </application_info>
  <settings>
    <setting>
      <name>ai_device_type</name>
      <value>GPU</value><!--Options: CPU, GPU -->
    </setting>
    <setting>
      <name>ai_inference_precision</name>
      <value>float32</value><!--Options: float32, float16, integer -->
    </setting>
  </settings>
</benchmark>


ai_computer_vision_coreml.def

Use this definition file to run the UL Procyon AI Computer Vision Benchmark with default settings and using Apple Core ML. Using this definition file is the same as running the benchmark from the GUI.

<?xml version="1.0" encoding="utf-8"?>
<benchmark>
	<test_info>
		<benchmark_tests>
			<benchmark_test name="AICoreMLBenchmark" test_run_type="EXPLICIT" version="1.0"/>
		</benchmark_tests>
	</test_info>
	<application_info>
		<selected_workloads>
			<selected_workload name="AIMobileNetV3Default"/>
		    <selected_workload name="AIInceptionV4Default"/>
			<selected_workload name="AIResNet50Default"/>
			<selected_workload name="AIDeepLabV3Default"/>
			<selected_workload name="AIYOLOV3Default"/>
			<selected_workload name="AIESRGANDefault"/>
		</selected_workloads>
	</application_info>
  <settings>
    <setting>
      <name>ai_device_type</name>
      <value>ALL</value> <!-- ALL, CPU, CPU_AND_GPU, CPU_AND_NE -->
    </setting>
    <setting>
      <name>ai_inference_precision</name>
      <value>float32</value> <!-- float32, float16, integer -->
    </setting>
  </settings>
</benchmark>