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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2403290-PTS-5900HXEO83
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March 29
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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 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: 1 - Model: AlexNet images/sec > Higher Is Better a . 4.61 |=================================================================== b . 4.72 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better a . 41.54 |================================================================== b . 42.63 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: AlexNet images/sec > Higher Is Better a . 57.09 |=================================================================== b . 58.04 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: AlexNet images/sec > Higher Is Better a . 69.68 |=================================================================== b . 70.84 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 13.04 |=================================================================== b . 13.20 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 5.33 |=================================================================== b . 5.48 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 21.87 |=================================================================== b . 22.10 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 7.85 |===================================================================== b . 7.87 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: GoogLeNet images/sec > Higher Is Better a . 21.78 |==================================================================== b . 21.90 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 images/sec > Higher Is Better a . 7.72 |==================================================================== b . 7.80 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: GoogLeNet images/sec > Higher Is Better a . 21.68 |==================================================================== b . 21.83 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 images/sec > Higher Is Better a . 7.69 |==================================================================== b . 7.84 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 33.77 |==================================================================== b . 33.06 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 15.49 |==================================================================== b . 15.18 |=================================================================== 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: 32 - Model: ResNet-50 batches/sec > Higher Is Better a . 19.66 |================================================================ b . 20.77 |==================================================================== 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: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 9.21 |===================================================================== b . 9.17 |===================================================================== 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: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 9.33 |=================================================================== b . 9.55 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.22 |==================================================================== b . 6.34 |===================================================================== 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: 64 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.22 |===================================================================== b . 5.90 |================================================================= Primesieve 12.1 Length: 1e12 Seconds < Lower Is Better a . 19.27 |==================================================================== b . 19.25 |==================================================================== Stockfish 16.1 Chess Benchmark Nodes Per Second > Higher Is Better a . 11509974 |========================================================== b . 12942804 |================================================================= SVT-AV1 2.0 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 3.635 |==================================================================== b . 3.654 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 26.06 |==================================================================== b . 26.00 |==================================================================== 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 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 12.93 |=================================================================== b . 13.03 |==================================================================== 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 |=================================================================== Blender 4.1 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 152.81 |================================================================== b . 154.22 |=================================================================== Blender 4.1 Blend File: Junkshop - Compute: CPU-Only Seconds < Lower Is Better a . 208.77 |=================================================================== b . 208.69 |=================================================================== Blender 4.1 Blend File: Classroom - Compute: CPU-Only Seconds < Lower Is Better a . 395.99 |=================================================================== b . 397.59 |=================================================================== Blender 4.1 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 186.33 |=================================================================== b . 185.76 |=================================================================== Blender 4.1 Blend File: Barbershop - Compute: CPU-Only Seconds < Lower Is Better a . 1474.59 |================================================================= b . 1490.95 |================================================================== Blender 4.1 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 481.62 |=================================================================== b . 482.13 |=================================================================== Timed Mesa Compilation 24.0 Time To Compile Seconds < Lower Is Better a . 44.56 |==================================================================== b . 43.99 |===================================================================