AMD Ryzen 9 5900X 12-Core testing with a ASUS ROG CROSSHAIR VIII HERO (3202 BIOS) and Sapphire AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 6GB on Ubuntu 20.10 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 2103138-SYST-5900XSY95
5900X sysbench onednn
AMD Ryzen 9 5900X 12-Core testing with a ASUS ROG CROSSHAIR VIII HERO (3202 BIOS) and Sapphire AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 6GB on Ubuntu 20.10 via the Phoronix Test Suite.
1:
Processor: AMD Ryzen 9 5900X 12-Core @ 3.70GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR VIII HERO (3202 BIOS), Chipset: AMD Starship/Matisse, Memory: 16GB, Disk: 1000GB Sabrent Rocket 4.0 Plus, Graphics: Sapphire AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 6GB (1780/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS VP28U, Network: Realtek RTL8125 2.5GbE + Intel I211
OS: Ubuntu 20.10, Kernel: 5.12.0-051200rc2-generic (x86_64) 20210306, Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.2.1 (LLVM 11.0.0), Vulkan: 1.2.131, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 3840x2160
2:
Processor: AMD Ryzen 9 5900X 12-Core @ 3.70GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR VIII HERO (3202 BIOS), Chipset: AMD Starship/Matisse, Memory: 16GB, Disk: 1000GB Sabrent Rocket 4.0 Plus, Graphics: Sapphire AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 6GB (1780/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS VP28U, Network: Realtek RTL8125 2.5GbE + Intel I211
OS: Ubuntu 20.10, Kernel: 5.12.0-051200rc2-generic (x86_64) 20210306, Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.2.1 (LLVM 11.0.0), Vulkan: 1.2.131, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 3840x2160
3:
Processor: AMD Ryzen 9 5900X 12-Core @ 3.70GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR VIII HERO (3202 BIOS), Chipset: AMD Starship/Matisse, Memory: 16GB, Disk: 1000GB Sabrent Rocket 4.0 Plus, Graphics: Sapphire AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 6GB (1780/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS VP28U, Network: Realtek RTL8125 2.5GbE + Intel I211
OS: Ubuntu 20.10, Kernel: 5.12.0-051200rc2-generic (x86_64) 20210306, Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.2.1 (LLVM 11.0.0), Vulkan: 1.2.131, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 3840x2160
oneDNN 2.1.2
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 3.75267 |==================================================================
2 . 3.77107 |==================================================================
3 . 3.77032 |==================================================================
oneDNN 2.1.2
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 8.62717 |==================================================================
2 . 7.53391 |==========================================================
3 . 7.53364 |==========================================================
oneDNN 2.1.2
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 1.06966 |==================================================================
2 . 1.06981 |==================================================================
3 . 1.07025 |==================================================================
oneDNN 2.1.2
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 0.524499 |========================================
2 . 0.862216 |=================================================================
3 . 0.517520 |=======================================
oneDNN 2.1.2
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 16.19 |====================================================================
2 . 15.72 |==================================================================
3 . 15.70 |==================================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 5.53845 |==================================================================
2 . 5.32047 |===============================================================
3 . 5.28668 |===============================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 4.27928 |==================================================================
2 . 4.26624 |==================================================================
3 . 4.28406 |==================================================================
oneDNN 2.1.2
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 17.35 |====================================================================
2 . 16.47 |=================================================================
3 . 16.49 |=================================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 1.31629 |==================================================================
2 . 1.30940 |==================================================================
3 . 1.31421 |==================================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 2.01613 |==================================================================
2 . 2.01320 |==================================================================
3 . 2.00925 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 2890.59 |==================================================================
2 . 2892.53 |==================================================================
3 . 2905.72 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 1672.05 |=================================================================
2 . 1689.61 |==================================================================
3 . 1679.32 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 2904.05 |==================================================================
2 . 2901.37 |=================================================================
3 . 2924.95 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 1707.04 |==================================================================
2 . 1698.31 |==================================================================
3 . 1701.38 |==================================================================
oneDNN 2.1.2
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 0.760181 |=================================================================
2 . 0.758823 |=================================================================
3 . 0.760394 |=================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
1 . 2897.91 |==================================================================
2 . 2873.62 |=================================================================
3 . 2875.28 |=================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
1 . 1697.37 |==================================================================
2 . 1701.82 |==================================================================
3 . 1693.14 |==================================================================
oneDNN 2.1.2
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 1.74083 |==================================================================
2 . 1.74073 |==================================================================
3 . 1.74045 |==================================================================
Sysbench 1.0.20
Test: RAM / Memory
MiB/sec > Higher Is Better
1 . 13950.10 |=================================================================
2 . 13926.31 |=================================================================
3 . 13917.98 |=================================================================
Sysbench 1.0.20
Test: CPU
Events Per Second > Higher Is Better
1 . 68475.65 |=================================================================
2 . 68421.77 |=================================================================
3 . 68422.23 |=================================================================