Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB 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 2311191-PTS-FS16700400
fs
Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.04 via the Phoronix Test Suite.
,,"s","b","c","d"
Processor,,Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads),Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads),Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads),Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads)
Motherboard,,Dell 0DXP1F (3.7.0 BIOS),Dell 0DXP1F (3.7.0 BIOS),Dell 0DXP1F (3.7.0 BIOS),Dell 0DXP1F (3.7.0 BIOS)
Chipset,,Intel Tiger Lake-LP,Intel Tiger Lake-LP,Intel Tiger Lake-LP,Intel Tiger Lake-LP
Memory,,16GB,16GB,16GB,16GB
Disk,,Micron 2300 NVMe 512GB,Micron 2300 NVMe 512GB,Micron 2300 NVMe 512GB,Micron 2300 NVMe 512GB
Graphics,,Intel Xe TGL GT2 15GB (1350MHz),Intel Xe TGL GT2 15GB (1350MHz),Intel Xe TGL GT2 15GB (1350MHz),Intel Xe TGL GT2 15GB (1350MHz)
Audio,,Realtek ALC289,Realtek ALC289,Realtek ALC289,Realtek ALC289
Network,,Intel Wi-Fi 6 AX201,Intel Wi-Fi 6 AX201,Intel Wi-Fi 6 AX201,Intel Wi-Fi 6 AX201
OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04
Kernel,,6.2.0-36-generic (x86_64),6.2.0-36-generic (x86_64),6.2.0-36-generic (x86_64),6.2.0-36-generic (x86_64)
Desktop,,GNOME Shell 42.2,GNOME Shell 42.2,GNOME Shell 42.2,GNOME Shell 42.2
Display Server,,X Server + Wayland,X Server + Wayland,X Server + Wayland,X Server + Wayland
OpenGL,,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1
OpenCL,,OpenCL 3.0,OpenCL 3.0,OpenCL 3.0,OpenCL 3.0
Vulkan,,1.3.204,1.3.204,1.3.204,1.3.204
Compiler,,GCC 11.4.0,GCC 11.4.0,GCC 11.4.0,GCC 11.4.0
File-System,,ext4,ext4,ext4,ext4
Screen Resolution,,1920x1200,1920x1200,1920x1200,1920x1200
,,"s","b","c","d"
"Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,1401.88,1405.37,1401.13,1402.14
"Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,1100.02,1103.33,1101.16,1113.84
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,528.21,528.72,528.01,528.78
"PyTorch - Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l (batches/sec)",HIB,4.10,4.12,4.12,4.11
"PyTorch - Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l (batches/sec)",HIB,4.10,4.11,4.12,4.12
"PyTorch - Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l (batches/sec)",HIB,4.11,4.12,4.12,4.11
"PyTorch - Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l (batches/sec)",HIB,4.13,4.08,4.12,4.12
"PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,4.08,4.11,4.13,4.13
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,417.28,417.64,416.74,416.31
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,5.49,5.63,5.62,5.58
"PyTorch - Device: CPU - Batch Size: 256 - Model: ResNet-152 (batches/sec)",HIB,5.55,5.60,5.59,5.62
"PyTorch - Device: CPU - Batch Size: 512 - Model: ResNet-152 (batches/sec)",HIB,5.56,5.59,5.59,5.62
"PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-152 (batches/sec)",HIB,5.54,5.61,5.61,5.62
"PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-152 (batches/sec)",HIB,5.57,5.58,5.61,5.62
"PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,7.37,7.32,7.36,7.33
"PyTorch - Device: CPU - Batch Size: 512 - Model: ResNet-50 (batches/sec)",HIB,13.83,13.74,13.81,13.77
"PyTorch - Device: CPU - Batch Size: 256 - Model: ResNet-50 (batches/sec)",HIB,13.90,13.76,13.81,13.68
"PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-50 (batches/sec)",HIB,13.82,13.75,13.79,13.79
"PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-50 (batches/sec)",HIB,13.86,13.65,13.79,13.53
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,14.23,13.78,13.78,13.81
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,31.08,30.15,30.62,24.75
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,11.51,9.93,10.97,9.79