onednn y 3990X AMD Ryzen Threadripper 3990X 64-Core testing with a Gigabyte TRX40 AORUS PRO WIFI (F4p BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 22.10 via the Phoronix Test Suite. A: Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F4p BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 22.10, Kernel: 6.0.0-060000rc7daily20220927-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.3 + Wayland, OpenGL: 4.6 Mesa 22.1.7 (LLVM 14.0.6 DRM 3.48), Vulkan: 1.3.211, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160 B: Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F4p BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 22.10, Kernel: 6.0.0-060000rc7daily20220927-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.3 + Wayland, OpenGL: 4.6 Mesa 22.1.7 (LLVM 14.0.6 DRM 3.48), Vulkan: 1.3.211, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160 C: Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F4p BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 22.10, Kernel: 6.0.0-060000rc7daily20220927-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.3 + Wayland, OpenGL: 4.6 Mesa 22.1.7 (LLVM 14.0.6 DRM 3.48), Vulkan: 1.3.211, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160 Y-Cruncher 0.7.10.9513 Pi Digits To Calculate: 1B Seconds < Lower Is Better A . 22.62 |==================================================================== B . 22.53 |==================================================================== C . 22.59 |==================================================================== Y-Cruncher 0.7.10.9513 Pi Digits To Calculate: 10B Seconds < Lower Is Better A . 277.64 |=================================================================== B . 277.50 |=================================================================== C . 277.87 |=================================================================== Y-Cruncher 0.7.10.9513 Pi Digits To Calculate: 500M Seconds < Lower Is Better A . 11.00 |==================================================================== B . 10.97 |==================================================================== C . 11.03 |==================================================================== oneDNN 2.7 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 2.46105 |================================================================== B . 1.61291 |=========================================== C . 1.64163 |============================================ oneDNN 2.7 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 5.34789 |================================================================== B . 5.31681 |================================================================== C . 5.35675 |================================================================== oneDNN 2.7 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 3.32556 |============================================================= B . 2.36497 |============================================ C . 3.58297 |================================================================== oneDNN 2.7 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 1.11141 |================================================================== B . 1.10316 |================================================================== C . 1.10834 |================================================================== oneDNN 2.7 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 0.963938 |================================================================= B . 0.850528 |========================================================= C . 0.948633 |================================================================ oneDNN 2.7 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 8.84997 |================================================================= B . 9.04081 |================================================================== C . 8.42061 |============================================================= oneDNN 2.7 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 2.08438 |================================================================== B . 2.09780 |================================================================== C . 2.08861 |================================================================== oneDNN 2.7 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 6.40545 |================================================================== B . 6.41234 |================================================================== C . 6.43985 |================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 1.78326 |============================================================= B . 1.87072 |================================================================ C . 1.92539 |================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 0.972299 |=============================================================== B . 0.996593 |================================================================= C . 0.984030 |================================================================ oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 5099.39 |================================================================== B . 5075.05 |================================================================== C . 5065.26 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 1290.42 |================================================================ B . 1252.43 |============================================================== C . 1329.45 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 5170.56 |================================================================== B . 5089.14 |================================================================= C . 5096.85 |================================================================= oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 1261.59 |================================================================= B . 1242.98 |================================================================ C . 1284.38 |================================================================== oneDNN 2.7 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 6.60041 |========================================== B . 6.25739 |======================================== C . 10.27400 |================================================================= oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better A . 5084.99 |================================================================== B . 5055.59 |================================================================== C . 5074.13 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better A . 1311.31 |================================================================== B . 1269.62 |================================================================ C . 1262.25 |================================================================ oneDNN 2.7 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 14.36 |==================================================================== B . 14.34 |==================================================================== C . 13.47 |================================================================