fghj AMD Ryzen 9 5900HX testing with a ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS) and ASUS AMD Cezanne 512MB on Ubuntu 22.10 via the Phoronix Test Suite. a: Processor: AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores / 16 Threads), Motherboard: ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 2 x 8 GB DDR4-3200MT/s Micron 4ATF1G64HZ-3G2E2, Disk: 512GB SAMSUNG MZVLQ512HBLU-00B00, Graphics: ASUS AMD Cezanne 512MB (2500/1000MHz), Audio: AMD Navi 21/23, Monitor: LQ156M1JW25, Network: Realtek RTL8111/8168/8411 + MEDIATEK MT7921 802.11ax PCI OS: Ubuntu 22.10, Kernel: 5.19.0-46-generic (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4 + Wayland, OpenGL: 4.6 Mesa 22.2.5 (LLVM 15.0.2 DRM 3.47), Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1080 b: Processor: AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores / 16 Threads), Motherboard: ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 2 x 8 GB DDR4-3200MT/s Micron 4ATF1G64HZ-3G2E2, Disk: 512GB SAMSUNG MZVLQ512HBLU-00B00, Graphics: ASUS AMD Cezanne 512MB, Audio: AMD Navi 21/23, Monitor: LQ156M1JW25, Network: Realtek RTL8111/8168/8411 + MEDIATEK MT7921 802.11ax PCI OS: Ubuntu 22.10, Kernel: 5.19.0-46-generic (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4 + Wayland, OpenGL: 4.6 Mesa 22.2.5 (LLVM 15.0.2 DRM 3.47), Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1080 c: Processor: AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores / 16 Threads), Motherboard: ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 2 x 8 GB DDR4-3200MT/s Micron 4ATF1G64HZ-3G2E2, Disk: 512GB SAMSUNG MZVLQ512HBLU-00B00, Graphics: ASUS AMD Cezanne 512MB (2500/1000MHz), Audio: AMD Navi 21/23, Monitor: LQ156M1JW25, Network: Realtek RTL8111/8168/8411 + MEDIATEK MT7921 802.11ax PCI OS: Ubuntu 22.10, Kernel: 5.19.0-46-generic (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4 + Wayland, OpenGL: 4.6 Mesa 22.2.5 (LLVM 15.0.2 DRM 3.47), Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1080 Y-Cruncher 0.8.3 Pi Digits To Calculate: 500M Seconds < Lower Is Better a . 23.26 |==================================================================== b . 23.08 |=================================================================== c . 22.89 |=================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 1B Seconds < Lower Is Better a . 50.42 |==================================================================== b . 49.83 |=================================================================== c . 49.80 |=================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: VGG-16 images/sec > Higher Is Better a . 1.43 |==================================================================== b . 1.45 |===================================================================== c . 1.46 |===================================================================== Quicksilver 20230818 Input: CORAL2 P2 Figure Of Merit > Higher Is Better a . 22560000 |================================================================= b . 22713333 |================================================================= c . 22536667 |================================================================ TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: AlexNet images/sec > Higher Is Better a . 4.61 |==================================================================== b . 4.69 |===================================================================== c . 4.71 |===================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: VGG-16 images/sec > Higher Is Better a . 3.50 |==================================================================== b . 3.52 |===================================================================== c . 3.54 |===================================================================== Quicksilver 20230818 Input: CORAL2 P1 Figure Of Merit > Higher Is Better a . 11990000 |================================================================= b . 11966667 |================================================================= c . 11953333 |================================================================= TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better a . 40.05 |=================================================================== b . 40.34 |==================================================================== c . 40.40 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 12.17 |==================================================================== b . 12.22 |==================================================================== c . 12.05 |=================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 5.09 |==================================================================== b . 5.13 |===================================================================== c . 5.15 |===================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 21.12 |==================================================================== b . 21.20 |==================================================================== c . 21.25 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 7.59 |==================================================================== b . 7.65 |===================================================================== c . 7.70 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 34.04 |=================================================================== b . 34.44 |==================================================================== c . 34.13 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 15.15 |=================================================================== b . 15.27 |==================================================================== c . 15.21 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 20.22 |==================================================================== b . 18.95 |================================================================ c . 19.76 |================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 9.09 |===================================================================== b . 9.07 |==================================================================== c . 9.14 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 9.58 |===================================================================== b . 9.46 |==================================================================== c . 9.48 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.22 |==================================================================== b . 6.28 |===================================================================== c . 6.30 |===================================================================== Speedb 2.7 Test: Random Fill Op/s > Higher Is Better a . 819366 |=================================================================== b . 821234 |=================================================================== c . 818673 |=================================================================== Speedb 2.7 Test: Random Read Op/s > Higher Is Better a . 51459190 |================================================================= b . 51062544 |================================================================ c . 51108888 |================================================================= Speedb 2.7 Test: Update Random Op/s > Higher Is Better a . 458594 |================================================================= b . 472342 |=================================================================== c . 474392 |=================================================================== Speedb 2.7 Test: Sequential Fill Op/s > Higher Is Better a . 933961 |================================================================== b . 935621 |================================================================== c . 944900 |=================================================================== Speedb 2.7 Test: Random Fill Sync Op/s > Higher Is Better a . 11900 |==================================================================== b . 6186 |=================================== c . 5060 |============================= Speedb 2.7 Test: Read While Writing Op/s > Higher Is Better a . 3035137 |================================================================== b . 2842258 |============================================================== c . 2960839 |================================================================ Speedb 2.7 Test: Read Random Write Random Op/s > Higher Is Better a . 1769691 |================================================================== b . 1776164 |================================================================== c . 1778569 |================================================================== Quicksilver 20230818 Input: CTS2 Figure Of Merit > Higher Is Better a . 11390000 |================================================================= b . 11406667 |================================================================= c . 11416667 |=================================================================