Tensorflow-Lite_FLOAT

Intel Core i7-9750H testing with a Dell 0F7T8V (1.14.0 BIOS) and NVIDIA GeForce RTX 2070 with Max-Q Design 8GB on EndeavourOS rolling via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2304136-EIRI-230412085
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RTX-2070MQ_UHD-630_i7-9750H
April 12 2023
  4 Minutes
RTX-2070MQ_UHD-630_i7-9750H-Xanmod
April 13 2023
  4 Minutes
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Tensorflow-Lite_FLOATOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-9750H @ 4.50GHz (6 Cores / 12 Threads)Dell 0F7T8V (1.14.0 BIOS)Intel Cannon Lake PCH32GB2000GB Samsung SSD 970 EVO Plus 2TB + 1000GB CT1000MX500SSD1NVIDIA GeForce RTX 2070 with Max-Q Design 8GBRealtek ALC3204Realtek Device 2502 + Intel-AC 9260EndeavourOS rolling6.2.10-arch1-1 (x86_64)6.2.10-x64v1-xanmod1-1 (x86_64)KDE Plasma 5.27.4X Server 1.21.1.8NVIDIA 530.41.034.6.0OpenCL 3.0 + OpenCL 3.0 CUDA 12.1.98GCC 12.2.1 20230201 + Clang 15.0.7 + LLVM 15.0.7 + CUDA 12.1ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelsDesktopDisplay ServerDisplay DriverOpenGLOpenCLCompilerFile-SystemScreen ResolutionTensorflow-Lite_FLOAT BenchmarksSystem Logs- RTX-2070MQ_UHD-630_i7-9750H: Transparent Huge Pages: always- RTX-2070MQ_UHD-630_i7-9750H-Xanmod: Transparent Huge Pages: madvise- RTX-2070MQ_UHD-630_i7-9750H: Scaling Governor: intel_pstate powersave (EPP: performance) - CPU Microcode: 0xf0 - RTX-2070MQ_UHD-630_i7-9750H-Xanmod: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xf0 - itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: vulnerable + mds: Vulnerable; SMT vulnerable + meltdown: Vulnerable + mmio_stale_data: Vulnerable + retbleed: Vulnerable + spec_store_bypass: Vulnerable + spectre_v1: Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers + spectre_v2: Vulnerable IBPB: disabled STIBP: disabled PBRSB-eIBRS: Not affected + srbds: Vulnerable + tsx_async_abort: Not affected

TensorFlow Lite

This is a benchmark of the TensorFlow Lite implementation focused on TensorFlow machine learning for mobile, IoT, edge, and other cases. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: Mobilenet FloatRTX-2070MQ_UHD-630_i7-9750H-XanmodRTX-2070MQ_UHD-630_i7-9750H10002000300040005000SE +/- 12.44, N = 3SE +/- 56.20, N = 34812.704422.46
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: Mobilenet FloatRTX-2070MQ_UHD-630_i7-9750H-XanmodRTX-2070MQ_UHD-630_i7-9750H8001600240032004000Min: 4792.38 / Avg: 4812.7 / Max: 4835.3Min: 4311.8 / Avg: 4422.46 / Max: 4494.87