lg AMD Ryzen 7 7840U testing with a Framework FRANMDCP07 (03.03 BIOS) and AMD Phoenix1 512MB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: AMD Ryzen 7 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: Framework FRANMDCP07 (03.03 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 512GB Western Digital WD PC SN740 SDDPNQD-512G, Graphics: AMD Phoenix1 512MB (2700/2800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2312160600.5d937f~oibaf~m (git-5d937f0 2023-12-16 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.56), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2256x1504 b: Processor: AMD Ryzen 7 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: Framework FRANMDCP07 (03.03 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 512GB Western Digital WD PC SN740 SDDPNQD-512G, Graphics: AMD Phoenix1 512MB (2700/2800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2312160600.5d937f~oibaf~m (git-5d937f0 2023-12-16 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.56), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2256x1504 c: Processor: AMD Ryzen 7 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: Framework FRANMDCP07 (03.03 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 512GB Western Digital WD PC SN740 SDDPNQD-512G, Graphics: AMD Phoenix1 512MB (2700/2800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2312160600.5d937f~oibaf~m (git-5d937f0 2023-12-16 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.56), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2256x1504 Quicksilver 20230818 Input: CTS2 Figure Of Merit > Higher Is Better a . 10580000 |=============================================================== b . 10910000 |================================================================= c . 10510000 |=============================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: VGG-16 images/sec > Higher Is Better a . 7.46 |===================================================================== b . 7.46 |===================================================================== c . 7.47 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 8.52 |===================================================================== b . 8.48 |===================================================================== c . 8.40 |==================================================================== Quicksilver 20230818 Input: CORAL2 P2 Figure Of Merit > Higher Is Better a . 21860000 |================================================================= b . 21860000 |================================================================= c . 20910000 |============================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 12.50 |==================================================================== b . 12.37 |=================================================================== c . 12.50 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 11.95 |==================================================================== b . 11.88 |==================================================================== c . 11.93 |==================================================================== Quicksilver 20230818 Input: CORAL2 P1 Figure Of Merit > Higher Is Better a . 11580000 |================================================================= b . 11610000 |================================================================= c . 11500000 |================================================================ TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 21.85 |==================================================================== b . 21.84 |==================================================================== c . 21.84 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 28.64 |================================================================== b . 27.86 |================================================================ c . 29.46 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 20.10 |==================================================================== b . 19.93 |=================================================================== c . 19.75 |=================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 1B Seconds < Lower Is Better a . 37.13 |=================================================================== b . 37.21 |=================================================================== c . 37.51 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: VGG-16 images/sec > Higher Is Better a . 3.42 |===================================================================== b . 3.42 |===================================================================== c . 3.41 |===================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 65.04 |=================================================================== b . 65.09 |==================================================================== c . 65.56 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 49.42 |=================================================================== b . 47.70 |================================================================= c . 50.00 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better a . 89.66 |==================================================================== b . 88.85 |=================================================================== c . 89.39 |==================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 500M Seconds < Lower Is Better a . 16.75 |==================================================================== b . 16.70 |==================================================================== c . 16.69 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 11.35 |=================================================================== b . 11.38 |==================================================================== c . 11.46 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: AlexNet images/sec > Higher Is Better a . 11.09 |==================================================================== b . 11.11 |==================================================================== c . 11.09 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 42.37 |==================================================================== b . 41.59 |=================================================================== c . 42.30 |====================================================================