Jetson Xavier AGX Graphics GLMark2 + TensorRT

ARMv8 rev 0 testing with a jetson-xavier and NVIDIA Tegra Xavier on Ubuntu 18.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/1812242-SYST-JETSONX39.

Jetson Xavier AGX Graphics GLMark2 + TensorRTProcessorMotherboardMemoryDiskGraphicsMonitorOSKernelDesktopDisplay ServerDisplay DriverOpenGLVulkanCompilerFile-SystemScreen ResolutionJetson AGX XavierARMv8 rev 0 @ 2.27GHz (8 Cores)jetson-xavier16384MB31GB HBG4a2NVIDIA Tegra XavierASUS VP28UUbuntu 18.044.9.108-tegra (aarch64)Unity 7.5.0X Server 1.19.6NVIDIA 31.0.24.6.01.1.76GCC 7.3.0 + CUDA 10.0ext41920x1080OpenBenchmarking.org- Scaling Governor: tegra_cpufreq schedutil

Jetson Xavier AGX Graphics GLMark2 + TensorRTglmark2: 1920 x 1080tensorrt-inference: VGG16 - FP16 - 4 - Disabledtensorrt-inference: VGG16 - FP16 - 8 - Disabledtensorrt-inference: VGG16 - INT8 - 4 - Disabledtensorrt-inference: VGG16 - INT8 - 8 - Disabledtensorrt-inference: VGG19 - FP16 - 4 - Disabledtensorrt-inference: VGG19 - FP16 - 8 - Disabledtensorrt-inference: VGG19 - INT8 - 4 - Disabledtensorrt-inference: VGG19 - INT8 - 8 - Disabledtensorrt-inference: VGG16 - FP16 - 16 - Disabledtensorrt-inference: VGG16 - FP16 - 32 - Disabledtensorrt-inference: VGG16 - INT8 - 16 - Disabledtensorrt-inference: VGG16 - INT8 - 32 - Disabledtensorrt-inference: VGG19 - FP16 - 16 - Disabledtensorrt-inference: VGG19 - FP16 - 32 - Disabledtensorrt-inference: VGG19 - INT8 - 16 - Disabledtensorrt-inference: VGG19 - INT8 - 32 - Disabledtensorrt-inference: AlexNet - FP16 - 4 - Disabledtensorrt-inference: AlexNet - FP16 - 8 - Disabledtensorrt-inference: AlexNet - INT8 - 4 - Disabledtensorrt-inference: AlexNet - INT8 - 8 - Disabledtensorrt-inference: AlexNet - FP16 - 16 - Disabledtensorrt-inference: AlexNet - FP16 - 32 - Disabledtensorrt-inference: AlexNet - INT8 - 16 - Disabledtensorrt-inference: AlexNet - INT8 - 32 - Disabledtensorrt-inference: ResNet50 - FP16 - 4 - Disabledtensorrt-inference: ResNet50 - FP16 - 8 - Disabledtensorrt-inference: ResNet50 - INT8 - 4 - Disabledtensorrt-inference: ResNet50 - INT8 - 8 - Disabledtensorrt-inference: GoogleNet - FP16 - 4 - Disabledtensorrt-inference: GoogleNet - FP16 - 8 - Disabledtensorrt-inference: GoogleNet - INT8 - 4 - Disabledtensorrt-inference: GoogleNet - INT8 - 8 - Disabledtensorrt-inference: ResNet152 - FP16 - 4 - Disabledtensorrt-inference: ResNet152 - FP16 - 8 - Disabledtensorrt-inference: ResNet152 - INT8 - 4 - Disabledtensorrt-inference: ResNet152 - INT8 - 8 - Disabledtensorrt-inference: ResNet50 - FP16 - 16 - Disabledtensorrt-inference: ResNet50 - FP16 - 32 - Disabledtensorrt-inference: ResNet50 - INT8 - 16 - Disabledtensorrt-inference: ResNet50 - INT8 - 32 - Disabledtensorrt-inference: GoogleNet - FP16 - 16 - Disabledtensorrt-inference: GoogleNet - FP16 - 32 - Disabledtensorrt-inference: GoogleNet - INT8 - 16 - Disabledtensorrt-inference: GoogleNet - INT8 - 32 - Disabledtensorrt-inference: ResNet152 - FP16 - 16 - Disabledtensorrt-inference: ResNet152 - FP16 - 32 - Disabledtensorrt-inference: ResNet152 - INT8 - 16 - Disabledtensorrt-inference: ResNet152 - INT8 - 32 - DisabledJetson AGX Xavier2861195.45215.68286.64341.20172.15184.43262.17296.94228.75246.76381.33449.96180.03201.53362.08390.57799.421246.70975.181236.731434.821900.361879.492665.62542.80582.36865.46944.46546.10863.23651.851049.23219.08234.84350.28407.01593.33613.051106.131184.50857.89955.661339.831622.46224.60253.34445.22485.22OpenBenchmarking.org

GLmark2

Resolution: 1920 x 1080

OpenBenchmarking.orgScore, More Is BetterGLmark2Resolution: 1920 x 1080Jetson AGX Xavier60012001800240030002861

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier4080120160200SE +/- 3.17, N = 12195.45

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: FP16 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier50100150200250SE +/- 3.36, N = 5215.68

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier60120180240300SE +/- 3.98, N = 3286.64

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: INT8 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier70140210280350SE +/- 1.08, N = 3341.20

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier4080120160200SE +/- 1.25, N = 3172.15

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: FP16 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier4080120160200SE +/- 2.36, N = 3184.43

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier60120180240300SE +/- 0.96, N = 3262.17

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: INT8 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: INT8 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier60120180240300SE +/- 1.42, N = 3296.94

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: FP16 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier50100150200250SE +/- 1.63, N = 3228.75

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier50100150200250SE +/- 0.17, N = 3246.76

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: INT8 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier80160240320400SE +/- 10.09, N = 12381.33

NVIDIA TensorRT Inference

Neural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier100200300400500SE +/- 4.97, N = 10449.96

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: FP16 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier4080120160200SE +/- 11.67, N = 10180.03

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier4080120160200SE +/- 1.68, N = 3201.53

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: INT8 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: INT8 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier80160240320400SE +/- 0.66, N = 3362.08

NVIDIA TensorRT Inference

Neural Network: VGG19 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier80160240320400SE +/- 1.67, N = 3390.57

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 97.79, N = 9799.42

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: FP16 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier30060090012001500SE +/- 45.66, N = 121246.70

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 55.83, N = 12975.18

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: INT8 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier30060090012001500SE +/- 99.61, N = 121236.73

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: FP16 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier30060090012001500SE +/- 89.56, N = 91434.82

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier400800120016002000SE +/- 23.33, N = 31900.36

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: INT8 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier400800120016002000SE +/- 91.41, N = 121879.49

NVIDIA TensorRT Inference

Neural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier6001200180024003000SE +/- 248.85, N = 92665.62

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier120240360480600SE +/- 0.39, N = 3542.80

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: FP16 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier130260390520650SE +/- 0.24, N = 3582.36

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 14.20, N = 3865.46

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: INT8 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 40.28, N = 12944.46

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier120240360480600SE +/- 96.56, N = 9546.10

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: FP16 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 14.25, N = 12863.23

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier140280420560700SE +/- 140.60, N = 12651.85

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: INT8 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 121.56, N = 101049.23

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier50100150200250SE +/- 3.18, N = 3219.08

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: FP16 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier50100150200250SE +/- 0.36, N = 3234.84

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson AGX Xavier80160240320400SE +/- 5.48, N = 3350.28

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: INT8 - Batch Size: 8 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 8 - DLA Cores: DisabledJetson AGX Xavier90180270360450SE +/- 6.98, N = 3407.01

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: FP16 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier130260390520650SE +/- 7.03, N = 3593.33

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier130260390520650SE +/- 9.12, N = 3613.05

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: INT8 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 11.53, N = 121106.13

NVIDIA TensorRT Inference

Neural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier30060090012001500SE +/- 6.54, N = 31184.50

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: FP16 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 55.00, N = 9857.89

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier2004006008001000SE +/- 14.46, N = 12955.66

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: INT8 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier30060090012001500SE +/- 152.29, N = 91339.83

NVIDIA TensorRT Inference

Neural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier30060090012001500SE +/- 5.04, N = 31622.46

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: FP16 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier50100150200250SE +/- 15.50, N = 9224.60

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier60120180240300SE +/- 2.84, N = 3253.34

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: INT8 - Batch Size: 16 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 16 - DLA Cores: DisabledJetson AGX Xavier100200300400500SE +/- 4.04, N = 3445.22

NVIDIA TensorRT Inference

Neural Network: ResNet152 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX Xavier110220330440550SE +/- 1.47, N = 3485.22

Phoronix Test Suite v10.8.4