3700X

AMD Ryzen 7 3700X 8-Core testing with a Gigabyte A320M-S2H-CF (F52a BIOS) and HIS AMD Radeon HD 7750/8740 / R7 250E 1GB 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 2009023-FI-3700X498660
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
R1
September 02 2020
  32 Minutes
R2
September 02 2020
  31 Minutes
R3
September 02 2020
  31 Minutes
Invert Hiding All Results Option
  31 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


3700XOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores / 16 Threads)Gigabyte A320M-S2H-CF (F52a BIOS)AMD Starship/Matisse8GB240GB TOSHIBA RC100HIS AMD Radeon HD 7750/8740 / R7 250E 1GBAMD Oland/Hainan/CapeVA2431Realtek RTL8111/8168/8411Ubuntu 20.045.9.0-050900rc1daily20200817-generic (x86_64) 20200816GNOME Shell 3.36.4X Server 1.20.8modesetting 1.20.84.5 Mesa 20.0.8 (LLVM 10.0.0)GCC 9.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen Resolution3700X BenchmarksSystem Logs- Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8701021- 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

R1R2R3Result OverviewPhoronix Test Suite100%100%100%101%101%TensorFlow LiteNAMDTensorFlow LiteTensorFlow LiteTensorFlow LiteTensorFlow LiteTensorFlow LiteNASNet MobileATPase Simulation - 327,506 AtomsMobilenet FloatI.R.VSqueezeNetInception V4Mobilenet Quant

3700Xnamd: ATPase Simulation - 327,506 Atomstensorflow-lite: SqueezeNettensorflow-lite: Inception V4tensorflow-lite: NASNet Mobiletensorflow-lite: Mobilenet Floattensorflow-lite: Mobilenet Quanttensorflow-lite: Inception ResNet V2R1R2R32.26358190706275807316606512823513105124991632.26056190663275602716720312806613096724968372.2571119056227577031666111281281310122496437OpenBenchmarking.org

NAMD

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD 2.14ATPase Simulation - 327,506 AtomsR1R2R30.50931.01861.52792.03722.5465SE +/- 0.00629, N = 3SE +/- 0.00600, N = 3SE +/- 0.00810, N = 32.263582.260562.25711
OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD 2.14ATPase Simulation - 327,506 AtomsR1R2R3246810Min: 2.25 / Avg: 2.26 / Max: 2.27Min: 2.25 / Avg: 2.26 / Max: 2.27Min: 2.24 / Avg: 2.26 / Max: 2.27

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: SqueezeNetR1R2R340K80K120K160K200KSE +/- 94.23, N = 3SE +/- 88.37, N = 3SE +/- 138.40, N = 3190706190663190562
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: SqueezeNetR1R2R330K60K90K120K150KMin: 190535 / Avg: 190706.33 / Max: 190860Min: 190513 / Avg: 190663.33 / Max: 190819Min: 190301 / Avg: 190562.33 / Max: 190772

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception V4R1R2R3600K1200K1800K2400K3000KSE +/- 4122.19, N = 3SE +/- 2468.40, N = 3SE +/- 3741.23, N = 3275807327560272757703
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception V4R1R2R3500K1000K1500K2000K2500KMin: 2749970 / Avg: 2758073.33 / Max: 2763440Min: 2751290 / Avg: 2756026.67 / Max: 2759600Min: 2752060 / Avg: 2757703.33 / Max: 2764780

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: NASNet MobileR1R2R340K80K120K160K200KSE +/- 609.26, N = 3SE +/- 2104.44, N = 3SE +/- 1258.69, N = 3166065167203166611
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: NASNet MobileR1R2R330K60K90K120K150KMin: 164847 / Avg: 166065 / Max: 166705Min: 164982 / Avg: 167203.33 / Max: 171410Min: 164402 / Avg: 166611.33 / Max: 168761

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet FloatR1R2R330K60K90K120K150KSE +/- 57.66, N = 3SE +/- 115.94, N = 3SE +/- 113.06, N = 3128235128066128128
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet FloatR1R2R320K40K60K80K100KMin: 128127 / Avg: 128235 / Max: 128324Min: 127844 / Avg: 128066 / Max: 128235Min: 127903 / Avg: 128128 / Max: 128260

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet QuantR1R2R330K60K90K120K150KSE +/- 59.14, N = 3SE +/- 62.41, N = 3SE +/- 10.41, N = 3131051130967131012
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet QuantR1R2R320K40K60K80K100KMin: 130934 / Avg: 131051.33 / Max: 131123Min: 130844 / Avg: 130966.67 / Max: 131048Min: 130995 / Avg: 131012.33 / Max: 131031

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception ResNet V2R1R2R3500K1000K1500K2000K2500KSE +/- 1187.02, N = 3SE +/- 2439.16, N = 3SE +/- 2120.80, N = 3249916324968372496437
OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception ResNet V2R1R2R3400K800K1200K1600K2000KMin: 2496790 / Avg: 2499163.33 / Max: 2500400Min: 2492220 / Avg: 2496836.67 / Max: 2500510Min: 2492320 / Avg: 2496436.67 / Max: 2499380