gpu-server-eu-report

AMD Ryzen Threadripper PRO 5955WX 16-Cores testing with a ASUS Pro WS WRX80E-SAGE SE WIFI II (1302 BIOS) and Gigabyte NVIDIA GeForce RTX 4090 24GB on Ubuntu 22.04 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 2404028-NE-GPUSERVER82
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Performance Per
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Date
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  Test
  Duration
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte
April 02
  44 Minutes
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AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte

Processor: AMD Ryzen Threadripper PRO 5955WX 16-Cores @ 4.00GHz (16 Cores / 32 Threads), Motherboard: ASUS Pro WS WRX80E-SAGE SE WIFI II (1302 BIOS), Chipset: AMD Starship/Matisse, Memory: 256GB, Disk: 4001GB Western Digital WD_BLACK SN850X 4000GB, Graphics: Gigabyte NVIDIA GeForce RTX 4090 24GB, Audio: NVIDIA Device 22ba, Network: 2 x Intel 10G X550T + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 22.04, Kernel: 6.5.0-26-generic (x86_64), Desktop: GNOME Shell 42.9, Display Server: X Server 1.21.1.4, Display Driver: NVIDIA, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 800x600

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa008205
Python Notes: Python 3.10.12
Security Notes: 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: Vulnerable: 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

gpu-server-eu-reportOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen Threadripper PRO 5955WX 16-Cores @ 4.00GHz (16 Cores / 32 Threads)ASUS Pro WS WRX80E-SAGE SE WIFI II (1302 BIOS)AMD Starship/Matisse256GB4001GB Western Digital WD_BLACK SN850X 4000GBGigabyte NVIDIA GeForce RTX 4090 24GBNVIDIA Device 22ba2 x Intel 10G X550T + Intel Wi-Fi 6 AX210/AX211/AX411Ubuntu 22.046.5.0-26-generic (x86_64)GNOME Shell 42.9X Server 1.21.1.4NVIDIAGCC 11.4.0ext4800x600ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerDisplay DriverCompilerFile-SystemScreen ResolutionGpu-server-eu-report BenchmarksSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa008205- Python 3.10.12- 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: Vulnerable: 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

gpu-server-eu-reportpytorch: NVIDIA CUDA GPU - 1 - ResNet-50pytorch: NVIDIA CUDA GPU - 1 - ResNet-152pytorch: NVIDIA CUDA GPU - 16 - ResNet-50pytorch: NVIDIA CUDA GPU - 32 - ResNet-50pytorch: NVIDIA CUDA GPU - 64 - ResNet-50pytorch: NVIDIA CUDA GPU - 16 - ResNet-152pytorch: NVIDIA CUDA GPU - 256 - ResNet-50pytorch: NVIDIA CUDA GPU - 32 - ResNet-152pytorch: NVIDIA CUDA GPU - 512 - ResNet-50pytorch: NVIDIA CUDA GPU - 64 - ResNet-152pytorch: NVIDIA CUDA GPU - 256 - ResNet-152pytorch: NVIDIA CUDA GPU - 512 - ResNet-152pytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 16 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 64 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_lAMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte214.6074.76213.53212.31213.6875.20213.5774.44211.6875.2275.1374.9338.7338.1238.0137.7638.0838.27OpenBenchmarking.org

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte50100150200250SE +/- 0.46, N = 3214.60MIN: 182.08 / MAX: 216.79

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte20406080100SE +/- 0.18, N = 374.76MIN: 68.57 / MAX: 75.86

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte50100150200250SE +/- 0.25, N = 3213.53MIN: 197.82 / MAX: 215.82

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte50100150200250SE +/- 0.36, N = 3212.31MIN: 199.16 / MAX: 214.97

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte50100150200250SE +/- 1.41, N = 3213.68MIN: 126.84 / MAX: 218.74

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte20406080100SE +/- 0.44, N = 375.20MIN: 68.59 / MAX: 76.29

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte50100150200250SE +/- 0.90, N = 3213.57MIN: 202.47 / MAX: 217.01

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte20406080100SE +/- 0.59, N = 374.44MIN: 67.59 / MAX: 76.29

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte50100150200250SE +/- 0.09, N = 3211.68MIN: 201.79 / MAX: 214.18

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte20406080100SE +/- 0.43, N = 375.22MIN: 68.96 / MAX: 76.24

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte20406080100SE +/- 0.36, N = 375.13MIN: 68.59 / MAX: 76.23

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte20406080100SE +/- 0.54, N = 374.93MIN: 68.82 / MAX: 76.5

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_lAMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte918273645SE +/- 0.36, N = 638.73MIN: 34.49 / MAX: 39.57

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_lAMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte918273645SE +/- 0.17, N = 338.12MIN: 34.52 / MAX: 38.69

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_lAMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte918273645SE +/- 0.46, N = 438.01MIN: 34.07 / MAX: 38.96

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_lAMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte918273645SE +/- 0.28, N = 1337.76MIN: 33.85 / MAX: 39.14

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_lAMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte918273645SE +/- 0.10, N = 338.08MIN: 34.82 / MAX: 38.49

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_lAMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte918273645SE +/- 0.18, N = 338.27MIN: 34.61 / MAX: 38.86

AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte

Processor: AMD Ryzen Threadripper PRO 5955WX 16-Cores @ 4.00GHz (16 Cores / 32 Threads), Motherboard: ASUS Pro WS WRX80E-SAGE SE WIFI II (1302 BIOS), Chipset: AMD Starship/Matisse, Memory: 256GB, Disk: 4001GB Western Digital WD_BLACK SN850X 4000GB, Graphics: Gigabyte NVIDIA GeForce RTX 4090 24GB, Audio: NVIDIA Device 22ba, Network: 2 x Intel 10G X550T + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 22.04, Kernel: 6.5.0-26-generic (x86_64), Desktop: GNOME Shell 42.9, Display Server: X Server 1.21.1.4, Display Driver: NVIDIA, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 800x600

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa008205
Python Notes: Python 3.10.12
Security Notes: 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: Vulnerable: 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

Testing initiated at 2 April 2024 12:40 by user gpu-server-eu.