Tests for a future article. Intel Core Ultra 7 155H testing with a MTL Swift SFG14-72T Coral_MTH (V1.01 BIOS) and Intel Arc MTL 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 2403270-NE-LDLD0728551
ldld
Tests for a future article. Intel Core Ultra 7 155H testing with a MTL Swift SFG14-72T Coral_MTH (V1.01 BIOS) and Intel Arc MTL 8GB on Ubuntu 23.10 via the Phoronix Test Suite.
a:
Processor: Intel Core Ultra 7 155H @ 4.80GHz (16 Cores / 22 Threads), Motherboard: MTL Swift SFG14-72T Coral_MTH (V1.01 BIOS), Chipset: Intel Device 7e7f, Memory: 8 x 2GB DRAM-6400MT/s Micron MT62F1G32D2DS-026, Disk: 1024GB Micron_2550_MTFDKBA1T0TGE, Graphics: Intel Arc MTL 8GB (2250MHz), Audio: Intel Meteor Lake-P HD Audio, Network: Intel Device 7e40
OS: Ubuntu 23.10, Kernel: 6.8.0-060800rc1daily20240126-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.1~git2401200600.ebcab1~oibaf~m (git-ebcab14 2024-01-20 mantic-oibaf-ppa), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200
b:
Processor: Intel Core Ultra 7 155H @ 4.80GHz (16 Cores / 22 Threads), Motherboard: MTL Swift SFG14-72T Coral_MTH (V1.01 BIOS), Chipset: Intel Device 7e7f, Memory: 8 x 2GB DRAM-6400MT/s Micron MT62F1G32D2DS-026, Disk: 1024GB Micron_2550_MTFDKBA1T0TGE, Graphics: Intel Arc MTL 8GB (2250MHz), Audio: Intel Meteor Lake-P HD Audio, Network: Intel Device 7e40
OS: Ubuntu 23.10, Kernel: 6.8.0-060800rc1daily20240126-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.1~git2401200600.ebcab1~oibaf~m (git-ebcab14 2024-01-20 mantic-oibaf-ppa), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200
Blender 4.1
Blend File: BMW27 - Compute: CPU-Only
Seconds < Lower Is Better
a . 163.16 |===================================================================
b . 161.09 |==================================================================
Blender 4.1
Blend File: Junkshop - Compute: CPU-Only
Seconds < Lower Is Better
a . 249.71 |===================================================================
b . 249.42 |===================================================================
Blender 4.1
Blend File: Fishy Cat - Compute: CPU-Only
Seconds < Lower Is Better
a . 234.47 |===================================================================
b . 230.59 |==================================================================
Blender 4.1
Blend File: Barbershop - Compute: CPU-Only
Seconds < Lower Is Better
a . 1770.95 |==================================================================
b . 1757.80 |==================================================================
Blender 4.1
Blend File: Pabellon Barcelona - Compute: CPU-Only
Seconds < Lower Is Better
a . 572.70 |==================================================================
b . 578.85 |===================================================================
Blender 4.1
Blend File: Classroom - Compute: CPU-Only
Seconds < Lower Is Better
a . 405.38 |==============================================================
b . 440.58 |===================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
a . 29.49 |====================================================================
b . 28.30 |=================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
a . 10.34 |====================================================================
b . 9.21 |=============================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
a . 16.03 |====================================================================
b . 15.93 |====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-50
batches/sec > Higher Is Better
a . 16.13 |====================================================================
b . 15.98 |===================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-50
batches/sec > Higher Is Better
a . 15.93 |====================================================================
b . 15.12 |=================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
a . 4.67 |===========================================================
b . 5.42 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: ResNet-50
batches/sec > Higher Is Better
a . 15.86 |====================================================================
b . 13.72 |===========================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-152
batches/sec > Higher Is Better
a . 5.93 |===================================================================
b . 6.12 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-152
batches/sec > Higher Is Better
a . 5.86 |=====================================================================
b . 5.59 |==================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: ResNet-152
batches/sec > Higher Is Better
a . 6.02 |====================================================================
b . 6.15 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 6.60 |=====================================================================
b . 6.50 |====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 3.07 |==========================================================
b . 3.68 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 3.49 |===================================================================
b . 3.59 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 3.78 |=====================================================================
b . 3.77 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 3.85 |=====================================================================
b . 3.69 |==================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: AlexNet
images/sec > Higher Is Better
a . 15.71 |====================================================================
b . 15.71 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
a . 92.70 |====================================================================
b . 91.49 |===================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: AlexNet
images/sec > Higher Is Better
a . 101.75 |===================================================================
b . 101.38 |===================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: AlexNet
images/sec > Higher Is Better
a . 104.18 |==================================================================
b . 106.50 |===================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: GoogLeNet
images/sec > Higher Is Better
a . 30.89 |====================================================================
b . 29.65 |=================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
images/sec > Higher Is Better
a . 7.91 |==========================================================
b . 9.41 |=====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
a . 48.05 |====================================================================
b . 47.93 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
a . 14.33 |====================================================================
b . 14.36 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: GoogLeNet
images/sec > Higher Is Better
a . 47.25 |====================================================================
b . 47.45 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: ResNet-50
images/sec > Higher Is Better
a . 14.77 |====================================================================
b . 14.75 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: GoogLeNet
images/sec > Higher Is Better
a . 46.51 |====================================================================
b . 46.41 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: ResNet-50
images/sec > Higher Is Better
a . 15.35 |====================================================================
b . 15.37 |====================================================================
Timed Mesa Compilation 24.0
Time To Compile
Seconds < Lower Is Better
a . 34.89 |====================================================================
b . 32.62 |================================================================