5900hx eo q1 Tests for a future article. 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 8GB 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 8GB 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 Blender 4.1 Blend File: Barbershop - Compute: CPU-Only Seconds < Lower Is Better a . 1474.59 |================================================================= b . 1490.95 |================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 images/sec > Higher Is Better a . 7.69 |==================================================================== b . 7.84 |===================================================================== Blender 4.1 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 481.62 |=================================================================== b . 482.13 |=================================================================== BRL-CAD 7.38.2 VGR Performance Metric VGR Performance Metric > Higher Is Better a . 155860 |=================================================================== b . 155503 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 images/sec > Higher Is Better a . 7.72 |==================================================================== b . 7.80 |===================================================================== Blender 4.1 Blend File: Classroom - Compute: CPU-Only Seconds < Lower Is Better a . 395.99 |=================================================================== b . 397.59 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: GoogLeNet images/sec > Higher Is Better a . 21.68 |==================================================================== b . 21.83 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.22 |===================================================================== b . 5.90 |================================================================= PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.22 |===================================================================== b . 6.18 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.22 |==================================================================== b . 6.34 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 7.85 |===================================================================== b . 7.87 |===================================================================== Blender 4.1 Blend File: Junkshop - Compute: CPU-Only Seconds < Lower Is Better a . 208.77 |=================================================================== b . 208.69 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better a . 9.15 |===================================================================== b . 8.69 |================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 batches/sec > Higher Is Better a . 8.67 |================================================================ b . 9.34 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 9.21 |===================================================================== b . 9.17 |===================================================================== Blender 4.1 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 186.33 |=================================================================== b . 185.76 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: GoogLeNet images/sec > Higher Is Better a . 21.78 |==================================================================== b . 21.90 |==================================================================== Stockfish 16.1 Chess Benchmark Nodes Per Second > Higher Is Better a . 11509974 |========================================================== b . 12942804 |================================================================= Blender 4.1 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 152.81 |================================================================== b . 154.22 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 9.33 |=================================================================== b . 9.55 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: AlexNet images/sec > Higher Is Better a . 69.68 |=================================================================== b . 70.84 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 19.76 |==================================================================== b . 19.22 |================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 batches/sec > Higher Is Better a . 20.11 |==================================================================== b . 18.59 |=============================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better a . 19.66 |================================================================ b . 20.77 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 21.87 |=================================================================== b . 22.10 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 15.49 |==================================================================== b . 15.18 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: AlexNet images/sec > Higher Is Better a . 57.09 |=================================================================== b . 58.04 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 3.635 |==================================================================== b . 3.654 |==================================================================== Timed Mesa Compilation 24.0 Time To Compile Seconds < Lower Is Better a . 44.56 |==================================================================== b . 43.99 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better a . 41.54 |================================================================== b . 42.63 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 33.77 |==================================================================== b . 33.06 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: AlexNet images/sec > Higher Is Better a . 4.61 |=================================================================== b . 4.72 |===================================================================== SVT-AV1 2.0 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 26.06 |==================================================================== b . 26.00 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 5.33 |=================================================================== b . 5.48 |===================================================================== Primesieve 12.1 Length: 1e12 Seconds < Lower Is Better a . 19.27 |==================================================================== b . 19.25 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 12.93 |=================================================================== b . 13.03 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 13.04 |=================================================================== b . 13.20 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 64.01 |==================================================================== b . 62.74 |=================================================================== SVT-AV1 2.0 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 65.50 |==================================================================== b . 64.38 |=================================================================== SVT-AV1 2.0 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 86.63 |==================================================================== b . 83.87 |================================================================== SVT-AV1 2.0 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 285.02 |=================================================================== b . 266.97 |=============================================================== SVT-AV1 2.0 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 329.50 |================================================================== b . 332.90 |===================================================================