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","2","3"
Processor,,AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads),AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads),AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads)
Motherboard,,MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS),MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS),MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS)
Chipset,,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse
Memory,,8GB,8GB,8GB
Disk,,256GB INTEL SSDPEKKW256G7,256GB INTEL SSDPEKKW256G7,256GB INTEL SSDPEKKW256G7
Graphics,,AMD FirePro V3800 512MB,AMD FirePro V3800 512MB,AMD FirePro V3800 512MB
Audio,,AMD Redwood HDMI Audio,AMD Redwood HDMI Audio,AMD Redwood HDMI Audio
Monitor,,DELL S2409W,DELL S2409W,DELL S2409W
Network,,Realtek RTL8111/8168/8411,Realtek RTL8111/8168/8411,Realtek RTL8111/8168/8411
OS,,Ubuntu 20.04,Ubuntu 20.04,Ubuntu 20.04
Kernel,,5.9.0-rc5-14sep-patch (x86_64) 20200914,5.9.0-rc5-14sep-patch (x86_64) 20200914,5.9.0-rc5-14sep-patch (x86_64) 20200914
Desktop,,GNOME Shell 3.36.4,GNOME Shell 3.36.4,GNOME Shell 3.36.4
Display Server,,X Server 1.20.9,X Server 1.20.9,X Server 1.20.9
OpenGL,,3.3 Mesa 20.0.8 (LLVM 10.0.0),3.3 Mesa 20.0.8 (LLVM 10.0.0),3.3 Mesa 20.0.8 (LLVM 10.0.0)
Compiler,,GCC 9.3.0,GCC 9.3.0,GCC 9.3.0
File-System,,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080
,,"1","2","3"
"Sysbench - Test: CPU (Events/sec)",HIB,8918.82,8918.55,8921.34
"SVT-HEVC - Tuning: 1 - Input: Bosphorus 1080p (FPS)",HIB,4.03,4.04,4.04
"SVT-HEVC - Tuning: 7 - Input: Bosphorus 1080p (FPS)",HIB,62.02,61.91,61.92
"SVT-HEVC - Tuning: 10 - Input: Bosphorus 1080p (FPS)",HIB,133.19,133.04,133.20
"SVT-VP9 - Tuning: VMAF Optimized - Input: Bosphorus 1080p (FPS)",HIB,108.00,109.62,109.10
"SVT-VP9 - Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p (FPS)",HIB,110.67,110.57,111.25
"SVT-VP9 - Tuning: Visual Quality Optimized - Input: Bosphorus 1080p (FPS)",HIB,87.76,88.03,87.67
"Sysbench - Test: RAM / Memory (MiB/sec)",HIB,16393.95,16345.46,16159.08
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,6.78051,6.75096,6.78600
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,10.4017,10.4706,10.2441
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.91753,4.90848,4.88115
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.73839,2.71709,2.68835
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,21.7320,21.8783,21.7457
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,11.04320,13.0095,13.0919
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,11.3315,11.3471,11.2956
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,22.6564,22.5345,22.6150
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,6.79725,6.78850,6.77109
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,9.15795,9.17290,9.15620
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,5993.82,5983.99,5981.79
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,3109.22,3118.20,3119.40
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,6032.29,6025.13,6008.78
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3101.94,3107.96,3113.52
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,5.02827,5.03340,5.01653
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,6030.31,6010.23,6015.97
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3113.93,3110.22,3102.45
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,6.09889,6.11621,6.12141