ldld 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 Timed Mesa Compilation 24.0 Time To Compile Seconds < Lower Is Better a . 34.89 |==================================================================== b . 32.62 |================================================================ 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 |==================================================================== 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 |===================================================================