AMD Ryzen 3 3300X 4-Core testing with a MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS) and AMD FirePro V3800 512MB on Ubuntu 20.04 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 2103158-HA-3300XONED31
3300X oneDNN SVT Stuff
AMD Ryzen 3 3300X 4-Core testing with a MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS) and AMD FirePro V3800 512MB on Ubuntu 20.04 via the Phoronix Test Suite.
1:
Processor: AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads), Motherboard: MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 256GB INTEL SSDPEKKW256G7, Graphics: AMD FirePro V3800 512MB, Audio: AMD Redwood HDMI Audio, Monitor: DELL S2409W, Network: Realtek RTL8111/8168/8411
OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 3.3 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
2:
Processor: AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads), Motherboard: MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 256GB INTEL SSDPEKKW256G7, Graphics: AMD FirePro V3800 512MB, Audio: AMD Redwood HDMI Audio, Monitor: DELL S2409W, Network: Realtek RTL8111/8168/8411
OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 3.3 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
3:
Processor: AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads), Motherboard: MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 256GB INTEL SSDPEKKW256G7, Graphics: AMD FirePro V3800 512MB, Audio: AMD Redwood HDMI Audio, Monitor: DELL S2409W, Network: Realtek RTL8111/8168/8411
OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 3.3 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
SVT-HEVC 1.5.0
Tuning: 1 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
1 . 4.03 |=====================================================================
2 . 4.04 |=====================================================================
3 . 4.04 |=====================================================================
SVT-HEVC 1.5.0
Tuning: 7 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
1 . 62.02 |====================================================================
2 . 61.91 |====================================================================
3 . 61.92 |====================================================================
SVT-HEVC 1.5.0
Tuning: 10 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
1 . 133.19 |===================================================================
2 . 133.04 |===================================================================
3 . 133.20 |===================================================================
SVT-VP9 0.3
Tuning: VMAF Optimized - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
1 . 108.00 |==================================================================
2 . 109.62 |===================================================================
3 . 109.10 |===================================================================
SVT-VP9 0.3
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
1 . 110.67 |===================================================================
2 . 110.57 |===================================================================
3 . 111.25 |===================================================================
SVT-VP9 0.3
Tuning: Visual Quality Optimized - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
1 . 87.76 |====================================================================
2 . 88.03 |====================================================================
3 . 87.67 |====================================================================
oneDNN 2.1.2
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 6.78051 |==================================================================
2 . 6.75096 |==================================================================
3 . 6.78600 |==================================================================
oneDNN 2.1.2
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 10.40 |====================================================================
2 . 10.47 |====================================================================
3 . 10.24 |===================================================================
oneDNN 2.1.2
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 4.91753 |==================================================================
2 . 4.90848 |==================================================================
3 . 4.88115 |==================================================================
oneDNN 2.1.2
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 2.73839 |==================================================================
2 . 2.71709 |=================================================================
3 . 2.68835 |=================================================================
oneDNN 2.1.2
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 21.73 |====================================================================
2 . 21.88 |====================================================================
3 . 21.75 |====================================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 11.04 |=========================================================
2 . 13.01 |====================================================================
3 . 13.09 |====================================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 11.33 |====================================================================
2 . 11.35 |====================================================================
3 . 11.30 |====================================================================
oneDNN 2.1.2
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 22.66 |====================================================================
2 . 22.53 |====================================================================
3 . 22.62 |====================================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 6.79725 |==================================================================
2 . 6.78850 |==================================================================
3 . 6.77109 |==================================================================
oneDNN 2.1.2
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 9.15795 |==================================================================
2 . 9.17290 |==================================================================
3 . 9.15620 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 5993.82 |==================================================================
2 . 5983.99 |==================================================================
3 . 5981.79 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 3109.22 |==================================================================
2 . 3118.20 |==================================================================
3 . 3119.40 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 6032.29 |==================================================================
2 . 6025.13 |==================================================================
3 . 6008.78 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 3101.94 |==================================================================
2 . 3107.96 |==================================================================
3 . 3113.52 |==================================================================
oneDNN 2.1.2
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 5.02827 |==================================================================
2 . 5.03340 |==================================================================
3 . 5.01653 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
1 . 6030.31 |==================================================================
2 . 6010.23 |==================================================================
3 . 6015.97 |==================================================================
oneDNN 2.1.2
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
1 . 3113.93 |==================================================================
2 . 3110.22 |==================================================================
3 . 3102.45 |==================================================================
oneDNN 2.1.2
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 6.09889 |==================================================================
2 . 6.11621 |==================================================================
3 . 6.12141 |==================================================================
Sysbench 1.0.20
Test: RAM / Memory
MiB/sec > Higher Is Better
1 . 16393.95 |=================================================================
2 . 16345.46 |=================================================================
3 . 16159.08 |================================================================
Sysbench 1.0.20
Test: CPU
Events Per Second > Higher Is Better
1 . 8918.82 |==================================================================
2 . 8918.55 |==================================================================
3 . 8921.34 |==================================================================