TensorFlow Lite AMD Ryzen Threadripper

AMD Ryzen Threadripper 3960X 24-Core testing with a MSI Creator TRX40 (MS-7C59) v1.0 (1.12N1 BIOS) and Sapphire AMD Radeon RX 5500/5500M / Pro 5500M 4GB on Ubuntu 20.04 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 2008237-FI-TENSORFLO23
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TR 3960X
August 23 2020
  19 Minutes
Vet 2
August 23 2020
  19 Minutes
Vet 3
August 23 2020
  19 Minutes
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TensorFlow Lite AMD Ryzen ThreadripperOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen Threadripper 3960X 24-Core @ 3.80GHz (24 Cores / 48 Threads)MSI Creator TRX40 (MS-7C59) v1.0 (1.12N1 BIOS)AMD Starship/Matisse32GB1000GB Sabrent Rocket 4.0 1TBSapphire AMD Radeon RX 5500/5500M / Pro 5500M 4GB (1900/875MHz)AMD Navi 10 HDMI AudioASUS MG28UAquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200Ubuntu 20.045.4.0-42-generic (x86_64)GNOME Shell 3.36.3GNOME Shell 3.36.4X Server 1.20.8modesetting 1.20.84.6 Mesa 20.0.8 (LLVM 10.0.0)GCC 9.3.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopsDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionTensorFlow Lite AMD Ryzen Threadripper BenchmarksSystem Logs- Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8301025- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected

TR 3960XVet 2Vet 3Result OverviewPhoronix Test Suite100%100%100%101%101%TensorFlow LiteTensorFlow LiteTensorFlow LiteTensorFlow LiteTensorFlow LiteTensorFlow LiteSqueezeNetMobilenet FloatMobilenet QuantInception V4NASNet MobileI.R.V

TensorFlow Lite AMD Ryzen Threadrippertensorflow-lite: SqueezeNettensorflow-lite: Inception V4tensorflow-lite: NASNet Mobiletensorflow-lite: Mobilenet Floattensorflow-lite: Mobilenet Quanttensorflow-lite: Inception ResNet V2TR 3960XVet 2Vet 376058.7113792386858.351035.552131.1100742375628.9113615786852.551344.752306.2100739375472.6113494386655.851110.652160.51006490OpenBenchmarking.org

TensorFlow Lite

This is a benchmark of the TensorFlow Lite implementation. 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 2020-08-23Model: SqueezeNetVet 3Vet 2TR 3960X16K32K48K64K80KSE +/- 295.88, N = 3SE +/- 329.17, N = 3SE +/- 97.87, N = 375472.675628.976058.7
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: SqueezeNetVet 3Vet 2TR 3960X13K26K39K52K65KMin: 74903.2 / Avg: 75472.63 / Max: 75896.8Min: 74987.8 / Avg: 75628.9 / Max: 76079.1Min: 75946.7 / Avg: 76058.67 / Max: 76253.7

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception V4Vet 3Vet 2TR 3960X200K400K600K800K1000KSE +/- 881.67, N = 3SE +/- 1424.48, N = 3SE +/- 688.10, N = 3113494311361571137923
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception V4Vet 3Vet 2TR 3960X200K400K600K800K1000KMin: 1133240 / Avg: 1134943.33 / Max: 1136190Min: 1133450 / Avg: 1136156.67 / Max: 1138280Min: 1137100 / Avg: 1137923.33 / Max: 1139290

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: NASNet MobileVet 3Vet 2TR 3960X20K40K60K80K100KSE +/- 271.25, N = 3SE +/- 118.06, N = 3SE +/- 144.60, N = 386655.886852.586858.3
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: NASNet MobileVet 3Vet 2TR 3960X15K30K45K60K75KMin: 86324.2 / Avg: 86655.77 / Max: 87193.4Min: 86632.6 / Avg: 86852.53 / Max: 87036.9Min: 86578.7 / Avg: 86858.3 / Max: 87062.1

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet FloatVet 3Vet 2TR 3960X11K22K33K44K55KSE +/- 192.51, N = 3SE +/- 73.95, N = 3SE +/- 148.03, N = 351110.651344.751035.5
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet FloatVet 3Vet 2TR 3960X9K18K27K36K45KMin: 50734.8 / Avg: 51110.6 / Max: 51371Min: 51270 / Avg: 51344.7 / Max: 51492.6Min: 50802.9 / Avg: 51035.47 / Max: 51310.4

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet QuantVet 3Vet 2TR 3960X11K22K33K44K55KSE +/- 104.73, N = 3SE +/- 124.19, N = 3SE +/- 72.23, N = 352160.552306.252131.1
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet QuantVet 3Vet 2TR 3960X9K18K27K36K45KMin: 52010 / Avg: 52160.47 / Max: 52361.9Min: 52091.7 / Avg: 52306.17 / Max: 52521.9Min: 52024.7 / Avg: 52131.07 / Max: 52268.9

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception ResNet V2Vet 3Vet 2TR 3960X200K400K600K800K1000KSE +/- 1302.93, N = 3SE +/- 761.50, N = 3SE +/- 450.42, N = 3100649010073931007423
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception ResNet V2Vet 3Vet 2TR 3960X200K400K600K800K1000KMin: 1004060 / Avg: 1006490 / Max: 1008520Min: 1006280 / Avg: 1007393.33 / Max: 1008850Min: 1006570 / Avg: 1007423.33 / Max: 1008100