pyt

AMD Ryzen Threadripper PRO 5965WX 24-Cores testing with a ASUS Pro WS WRX80E-SAGE SE WIFI (1201 BIOS) and ASUS NVIDIA NV106 2GB on Ubuntu 23.10 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 2311165-NE-PYT74848100
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
Show Result Confidence Charts
Allow Limiting Results To Certain Suite(s)

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
Toggle/Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
a
November 16 2023
  46 Minutes
b
November 16 2023
  46 Minutes
c
November 17 2023
  46 Minutes
Invert Behavior (Only Show Selected Data)
  46 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):


pytOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen Threadripper PRO 5965WX 24-Cores @ 3.80GHz (24 Cores / 48 Threads)ASUS Pro WS WRX80E-SAGE SE WIFI (1201 BIOS)AMD Starship/Matisse128GB2048GB SOLIDIGM SSDPFKKW020X7ASUS NVIDIA NV106 2GBAMD Starship/MatisseVA24312 x Intel X550 + Intel Wi-Fi 6 AX200Ubuntu 23.106.5.0-10-generic (x86_64)GNOME Shell 45.0X Server + Waylandnouveau4.3 Mesa 23.2.1-1ubuntu3GCC 13.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionPyt BenchmarksSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa008205- Python 3.11.6- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of safe RET no microcode + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

abcResult OverviewPhoronix Test Suite100%101%102%102%103%PyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchCPU - 32 - ResNet-50CPU - 32 - ResNet-152CPU - 256 - ResNet-50CPU - 1 - ResNet-152CPU - 16 - Efficientnet_v2_lCPU - 16 - ResNet-152CPU - 64 - ResNet-50CPU - 512 - ResNet-50CPU - 1 - ResNet-50CPU - 1 - Efficientnet_v2_lCPU - 512 - ResNet-152CPU - 32 - Efficientnet_v2_lCPU - 256 - ResNet-152CPU - 64 - Efficientnet_v2_lCPU - 512 - Efficientnet_v2_lCPU - 16 - ResNet-50CPU - 64 - ResNet-152CPU - 256 - Efficientnet_v2_l

pytpytorch: CPU - 32 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 16 - ResNet-152pytorch: CPU - 64 - ResNet-50pytorch: CPU - 512 - ResNet-50pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 512 - ResNet-152pytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 256 - ResNet-152pytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lpytorch: CPU - 16 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - Efficientnet_v2_labc31.1912.6032.4115.787.0612.6131.9032.0840.499.6712.466.9312.426.986.9831.7712.456.9932.1712.2932.0015.827.0412.4531.6732.1740.329.6912.376.9912.336.956.9931.9512.487.0032.2012.5231.7016.126.9512.4231.4732.5140.809.5912.356.9312.376.936.9531.9112.486.99OpenBenchmarking.org

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50abc71421283531.1932.1732.20MIN: 26.98 / MAX: 32.29MIN: 30.23 / MAX: 32.41MIN: 30.06 / MAX: 32.51

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152bca369121512.2912.5212.60MIN: 11.92 / MAX: 12.37MIN: 12.14 / MAX: 12.59MIN: 12.25 / MAX: 12.67

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50cba81624324031.7032.0032.41MIN: 29.83 / MAX: 32.04MIN: 27.01 / MAX: 32.27MIN: 30.42 / MAX: 32.66

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152abc4812162015.7815.8216.12MIN: 13.65 / MAX: 16MIN: 15.34 / MAX: 15.9MIN: 15.63 / MAX: 16.18

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lcba2468106.957.047.06MIN: 6.84 / MAX: 6.99MIN: 6.94 / MAX: 7.07MIN: 6.96 / MAX: 7.09

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152cba369121512.4212.4512.61MIN: 12.08 / MAX: 12.5MIN: 12.05 / MAX: 12.53MIN: 11.48 / MAX: 12.74

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50cba71421283531.4731.6731.90MIN: 29.63 / MAX: 31.67MIN: 29.72 / MAX: 31.94MIN: 28.18 / MAX: 32.3

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50abc81624324032.0832.1732.51MIN: 30.03 / MAX: 32.31MIN: 30.04 / MAX: 32.45MIN: 28.02 / MAX: 32.79

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50bac91827364540.3240.4940.80MIN: 37.53 / MAX: 40.57MIN: 36.35 / MAX: 40.84MIN: 37.94 / MAX: 41.03

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lcab36912159.599.679.69MIN: 9.39 / MAX: 9.62MIN: 9.48 / MAX: 9.72MIN: 9.49 / MAX: 9.73

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152cba369121512.3512.3712.46MIN: 10.69 / MAX: 12.45MIN: 12.07 / MAX: 12.44MIN: 12.15 / MAX: 12.52

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lacb2468106.936.936.99MIN: 6.83 / MAX: 6.96MIN: 6.36 / MAX: 6.96MIN: 6.14 / MAX: 7.09

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152bca369121512.3312.3712.42MIN: 12 / MAX: 12.45MIN: 12.04 / MAX: 12.42MIN: 12.09 / MAX: 12.48

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lcba2468106.936.956.98MIN: 6.83 / MAX: 6.97MIN: 6.85 / MAX: 6.98MIN: 6.87 / MAX: 7.01

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lcab2468106.956.986.99MIN: 6.84 / MAX: 6.97MIN: 6.87 / MAX: 7.01MIN: 6.89 / MAX: 7.02

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50acb71421283531.7731.9131.95MIN: 28.82 / MAX: 32.17MIN: 30.03 / MAX: 32.14MIN: 29.97 / MAX: 32.29

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152abc369121512.4512.4812.48MIN: 12.16 / MAX: 12.53MIN: 12.14 / MAX: 12.58MIN: 12.17 / MAX: 12.57

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lacb2468106.996.997.00MIN: 6.47 / MAX: 7.04MIN: 6.92 / MAX: 7.03MIN: 6.89 / MAX: 7.03