oidn onednn Intel Core i9-13900K testing with a ASUS PRIME Z790-P WIFI (0812 BIOS) and AMD Radeon RX 7900 XTX 24GB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (0812 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-7-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 b: Processor: Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (0812 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-7-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 c: Processor: Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (0812 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-7-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: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 1091.63 |================================================================== b . 1094.82 |================================================================== c . 1083.28 |================================================================= oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1092.27 |================================================================== b . 1079.34 |================================================================= c . 1088.58 |================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.33 |===================================================================== b . 0.33 |===================================================================== c . 0.33 |===================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 2138.32 |================================================================== b . 2125.44 |================================================================= c . 2154.15 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2139.93 |================================================================= b . 2117.34 |================================================================= c . 2164.01 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 2109.87 |================================================================= b . 2123.00 |================================================================= c . 2155.38 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 6.75811 |=============================================================== b . 6.83282 |=============================================================== c . 7.12042 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 1107.24 |================================================================== b . 1105.66 |================================================================== c . 1079.33 |================================================================ oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 0.992953 |================================================================ b . 0.992269 |================================================================ c . 1.007215 |================================================================= Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.67 |===================================================================== b . 0.67 |===================================================================== c . 0.67 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.67 |===================================================================== b . 0.67 |===================================================================== c . 0.67 |===================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.59380 |================================================================== b . 1.58094 |================================================================= c . 1.56556 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 4.04436 |================================================================== b . 3.97624 |================================================================= c . 3.99314 |================================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 1.83494 |============================================================ b . 2.01307 |================================================================== c . 1.97625 |================================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 0.693736 |============================================================== b . 0.722680 |================================================================= c . 0.687603 |============================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 4.12616 |================================================================= b . 4.17964 |================================================================== c . 4.14179 |================================================================= oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 0.695792 |================================================================ b . 0.703904 |================================================================= c . 0.698515 |================================================================= oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 6.00104 |=============================================================== b . 5.95660 |=============================================================== c . 6.24231 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 5.92499 |================================================================== b . 5.96397 |================================================================== c . 5.86711 |=================================================================