AMD Ryzen Threadripper 7980X 64-Cores testing with a ASUS Pro WS TRX50-SAGE WIFI (0217 BIOS) and AMD Radeon RX 7900 XT 20GB 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 2401079-PTS-BIGBENCH30
big bench
AMD Ryzen Threadripper 7980X 64-Cores testing with a ASUS Pro WS TRX50-SAGE WIFI (0217 BIOS) and AMD Radeon RX 7900 XT 20GB on Ubuntu 23.10 via the Phoronix Test Suite.
,,"a","b","c"
Processor,,AMD Ryzen Threadripper 7980X 64-Cores @ 8.21GHz (64 Cores / 128 Threads),AMD Ryzen Threadripper 7980X 64-Cores @ 8.21GHz (64 Cores / 128 Threads),AMD Ryzen Threadripper 7980X 64-Cores @ 8.21GHz (64 Cores / 128 Threads)
Motherboard,,ASUS Pro WS TRX50-SAGE WIFI (0217 BIOS),ASUS Pro WS TRX50-SAGE WIFI (0217 BIOS),ASUS Pro WS TRX50-SAGE WIFI (0217 BIOS)
Chipset,,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4
Memory,,128GB,128GB,128GB
Disk,,2000GB Corsair MP700 PRO + 1000GB Western Digital WDS100T1X0E-00AFY0,2000GB Corsair MP700 PRO + 1000GB Western Digital WDS100T1X0E-00AFY0,2000GB Corsair MP700 PRO + 1000GB Western Digital WDS100T1X0E-00AFY0
Graphics,,AMD Radeon RX 7900 XT 20GB (2025/1249MHz),AMD Radeon RX 7900 XT 20GB (2025/1249MHz),AMD Radeon RX 7900 XT 20GB (2025/1249MHz)
Audio,,Realtek ALC1220,Realtek ALC1220,Realtek ALC1220
Monitor,,DELL U2723QE,DELL U2723QE,DELL U2723QE
Network,,Aquantia Device 04c0 + Intel I226-LM + MEDIATEK MT7922 802.11ax PCI,Aquantia Device 04c0 + Intel I226-LM + MEDIATEK MT7922 802.11ax PCI,Aquantia Device 04c0 + Intel I226-LM + MEDIATEK MT7922 802.11ax PCI
OS,,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10
Kernel,,6.7.0-060700rc2daily20231126-generic (x86_64),6.7.0-060700rc2daily20231126-generic (x86_64),6.7.0-060700rc2daily20231126-generic (x86_64)
Desktop,,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0
Display Server,,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland
OpenGL,,4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.56),4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.56),4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.56)
Compiler,,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0
File-System,,ext4,ext4,ext4
Screen Resolution,,3840x2160,3840x2160,3840x2160
,,"a","b","c"
"PyTorch - Device: CPU - Batch Size: 256 - Model: ResNet-50 (batches/sec)",HIB,47.43,47.24,43.07
"TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,226.85,231.61,222.04
"PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-152 (batches/sec)",HIB,18.69,18.62,19.38
"TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,21.82,22.59,22.37
"PyTorch - Device: CPU - Batch Size: 512 - Model: ResNet-50 (batches/sec)",HIB,47.54,45.97,46.60
"PyTorch - Device: CPU - Batch Size: 512 - Model: ResNet-152 (batches/sec)",HIB,18.96,18.49,18.82
"PyTorch - Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l (batches/sec)",HIB,7.47,7.40,7.54
"PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-152 (batches/sec)",HIB,18.76,18.67,19.02
"PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-50 (batches/sec)",HIB,47.47,47.24,48.12
"PyTorch - Device: CPU - Batch Size: 256 - Model: ResNet-152 (batches/sec)",HIB,18.99,18.80,19.10
"PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-50 (batches/sec)",HIB,47.57,47.22,47.81
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,59.04,59.22,59.69
"TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,7.19,7.26,7.25
"PyTorch - Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l (batches/sec)",HIB,7.46,7.45,7.52
"PyTorch - Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l (batches/sec)",HIB,7.49,7.45,7.52
"TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,25.72,25.81,25.96
"PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,12.19,12.29,12.27
"PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,7.52,7.46,7.50
"PyTorch - Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l (batches/sec)",HIB,7.47,7.52,7.48
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,21.94,21.91,21.80
"Quicksilver - Input: CTS2 (Figure Of Merit)",HIB,20023333,19973333,20090000
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,54.70,54.44,54.72
"TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,1145.66,1148.38,1151.27
"TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,69.43,69.49,69.17
"Quicksilver - Input: CORAL2 P2 (Figure Of Merit)",HIB,19776667,19733333,19820000
"TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,510.66,508.52,510.4
"Quicksilver - Input: CORAL2 P1 (Figure Of Merit)",HIB,26026667,26010000,25920000
"TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,1070.73,1073.52,1075.09
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,47.47,47.41,47.60
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,18.68,18.65,18.71
"TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,187.92,188.5,188.52
"TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,80.0,79.77,79.87
"TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,272.16,272.22,272.84
"TensorFlow - Device: CPU - Batch Size: 32 - Model: VGG-16 (images/sec)",HIB,48.89,48.93,48.81
"TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,9.74,9.73,9.72
"TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,44.41,44.5,44.48
"TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,740.46,741.77,741.04
"TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec)",HIB,315.49,315.83,316.04
"TensorFlow - Device: CPU - Batch Size: 64 - Model: VGG-16 (images/sec)",HIB,52.95,53,52.91
"TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,311.60,311.23,311.73
"TensorFlow - Device: CPU - Batch Size: 256 - Model: VGG-16 (images/sec)",HIB,57.14,57.11,57.15
"TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,311.97,312.08,312.14
"TensorFlow - Device: CPU - Batch Size: 512 - Model: ResNet-50 (images/sec)",HIB,95.05,95.08,95.04
"TensorFlow - Device: CPU - Batch Size: 512 - Model: VGG-16 (images/sec)",HIB,57.97,57.97,57.99
"TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec)",HIB,91.12,91.13,91.11