one ryzen
AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and AMD Radeon RX 7900 XT/7900 XTX on Ubuntu 23.10 via the Phoronix Test Suite.


a: 

	Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: 1000GB Western Digital WDS100T1X0E-00AFY0 + 4001GB Western Digital WD_BLACK SN850X 4000GB + 64GB Flash Drive, Graphics: AMD Radeon RX 7900 XT/7900 XTX (2304/1249MHz), Audio: AMD Navi 31 HDMI/DP, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

	OS: Ubuntu 23.10, Kernel: 6.5.0-9-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server + Wayland, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160

b: 

	Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: 1000GB Western Digital WDS100T1X0E-00AFY0 + 4001GB Western Digital WD_BLACK SN850X 4000GB + 64GB Flash Drive, Graphics: AMD Radeon RX 7900 XT/7900 XTX (2304/1249MHz), Audio: AMD Navi 31 HDMI/DP, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

	OS: Ubuntu 23.10, Kernel: 6.5.0-9-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160


oneDNN 3.3
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 3.91295 |==================================================================
b . 1.87379 |================================


oneDNN 3.3
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 4.30649 |==================================================================
b . 3.55675 |=======================================================


Intel Open Image Denoise 2.1
Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only
Images / Sec > Higher Is Better
a . 0.40 |================================================================
b . 0.43 |=====================================================================


Intel Open Image Denoise 2.1
Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only
Images / Sec > Higher Is Better
a . 0.84 |================================================================
b . 0.90 |=====================================================================


Intel Open Image Denoise 2.1
Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only
Images / Sec > Higher Is Better
a . 0.85 |=================================================================
b . 0.90 |=====================================================================


oneDNN 3.3
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 0.400961 |=================================================================
b . 0.385854 |===============================================================


oneDNN 3.3
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 3.03045 |==================================================================
b . 2.95984 |================================================================


oneDNN 3.3
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 0.491923 |================================================================
b . 0.500464 |=================================================================


oneDNN 3.3
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 649.90 |===================================================================
b . 641.85 |==================================================================


oneDNN 3.3
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 1.48877 |==================================================================
b . 1.47641 |=================================================================


oneDNN 3.3
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 1.65499 |==================================================================
b . 1.64202 |=================================================================


oneDNN 3.3
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 2.58026 |==================================================================
b . 2.56592 |==================================================================


oneDNN 3.3
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 2.45723 |==================================================================
b . 2.46953 |==================================================================


oneDNN 3.3
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 641.86 |===================================================================
b . 644.81 |===================================================================


oneDNN 3.3
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 0.442267 |=================================================================
b . 0.440542 |=================================================================


oneDNN 3.3
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 0.672334 |=================================================================
b . 0.670009 |=================================================================


oneDNN 3.3
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 1255.35 |==================================================================
b . 1251.17 |==================================================================


oneDNN 3.3
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 5.68810 |==================================================================
b . 5.70396 |==================================================================


oneDNN 3.3
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 1.97222 |==================================================================
b . 1.96792 |==================================================================


oneDNN 3.3
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 1252.05 |==================================================================
b . 1253.71 |==================================================================


oneDNN 3.3
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 1253.77 |==================================================================
b . 1252.53 |==================================================================


oneDNN 3.3
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 0.618081 |=================================================================
b . 0.618601 |=================================================================


oneDNN 3.3
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 6.16304 |==================================================================
b . 6.15854 |==================================================================


oneDNN 3.3
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 640.36 |===================================================================
b . 640.38 |===================================================================