AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and NVIDIA NV174 8GB 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 2401073-PTS-TPY9619764
tpy
AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and NVIDIA NV174 8GB on Ubuntu 23.10 via the Phoronix Test Suite.
,,"a","b","c","d"
Processor,,AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads)
Motherboard,,ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS)
Chipset,,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8
Memory,,32GB,32GB,32GB,32GB
Disk,,2000GB Samsung SSD 980 PRO 2TB + 4001GB Western Digital WD_BLACK SN850X 4000GB,2000GB Samsung SSD 980 PRO 2TB + 4001GB Western Digital WD_BLACK SN850X 4000GB,2000GB Samsung SSD 980 PRO 2TB + 4001GB Western Digital WD_BLACK SN850X 4000GB,2000GB Samsung SSD 980 PRO 2TB + 4001GB Western Digital WD_BLACK SN850X 4000GB
Graphics,,NVIDIA NV174 8GB,NVIDIA NV174 8GB,NVIDIA NV174 8GB,NVIDIA NV174 8GB
Audio,,NVIDIA GA104 HD Audio,NVIDIA GA104 HD Audio,NVIDIA GA104 HD Audio,NVIDIA GA104 HD Audio
Monitor,,DELL U2723QE,DELL U2723QE,DELL U2723QE,DELL U2723QE
Network,,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411
OS,,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10
Kernel,,6.7.0-060700rc2daily20231127-generic (x86_64),6.7.0-060700rc2daily20231127-generic (x86_64),6.7.0-060700rc2daily20231127-generic (x86_64),6.7.0-060700rc2daily20231127-generic (x86_64)
Desktop,,GNOME Shell 45.1,GNOME Shell 45.1,GNOME Shell 45.1,GNOME Shell 45.1
Display Server,,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland
Display Driver,,nouveau,nouveau,nouveau,nouveau
OpenGL,,4.3 Mesa 24.0~git2311260600.945288~oibaf~m (git-945288f 2023-11-26 mantic-oibaf-ppa),4.3 Mesa 24.0~git2311260600.945288~oibaf~m (git-945288f 2023-11-26 mantic-oibaf-ppa),4.3 Mesa 24.0~git2311260600.945288~oibaf~m (git-945288f 2023-11-26 mantic-oibaf-ppa),4.3 Mesa 24.0~git2311260600.945288~oibaf~m (git-945288f 2023-11-26 mantic-oibaf-ppa)
Compiler,,GCC 13.2.0 + LLVM 16.0.6,GCC 13.2.0 + LLVM 16.0.6,GCC 13.2.0 + LLVM 16.0.6,GCC 13.2.0 + LLVM 16.0.6
File-System,,ext4,ext4,ext4,ext4
Screen Resolution,,3840x2160,3840x2160,3840x2160,3840x2160
,,"a","b","c","d"
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,31.52,31.43,30.27,29.64
"Speedb - Test: Read While Writing (Op/s)",HIB,5742331,5429438,5484728,5554254
"Speedb - Test: Random Fill Sync (Op/s)",HIB,3763,3753,3737,3645
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,50.47,50.64,49.49,50.46
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,75.35,75.88,76.25,74.61
"PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,16.63,16.92,16.61,16.79
"Speedb - Test: Random Fill (Op/s)",HIB,954442,939009,952620,937049
"Speedb - Test: Random Read (Op/s)",HIB,147210519,146512383,146079090,145109573
"TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,53.74,54.38,53.71,54.04
"Speedb - Test: Read Random Write Random (Op/s)",HIB,3121462,3139533,3144190,3154171
"Speedb - Test: Sequential Fill (Op/s)",HIB,981469,979943,989483,986432
"Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,16.673,16.798,16.817,16.833
"Quicksilver - Input: CORAL2 P1 (Figure Of Merit)",HIB,25220000,25120000,25110000,25020000
"Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,7.967,7.967,7.963,8.025
"PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,12.60,12.54,12.59,12.63
"Quicksilver - Input: CTS2 (Figure Of Merit)",HIB,21000000,21010000,20880000,20930000
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,21.04,20.93,20.91,21.03
"Speedb - Test: Update Random (Op/s)",HIB,685228,685969,689457,686870
"TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,15.99,15.97,16.04,16.01
"TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,14.58,14.59,14.63,14.63
"TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,18.86,18.84,18.83,18.8
"Quicksilver - Input: CORAL2 P2 (Figure Of Merit)",HIB,25790000,25790000,25760000,25710000
"Y-Cruncher - Pi Digits To Calculate: 5B (sec)",LIB,100.858,101.087,101.153,100.931
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,42.72,42.64,42.76,42.68
"TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,144.31,143.92,144.06,144.18
"TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,5.66,5.67,5.66,5.66
"TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,175.11,175.03,175.11,175.08