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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2209285-PTS-ONEDNNY340
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 |================================================================