sysbench onednn icelake

Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus G7 3GB on Ubuntu 20.10 via the Phoronix Test Suite.

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March 13 2021
  1 Hour, 11 Minutes
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March 13 2021
  1 Hour, 13 Minutes
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March 13 2021
  1 Hour, 7 Minutes
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sysbench onednn icelake Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus G7 3GB on Ubuntu 20.10 via the Phoronix Test Suite. 1: Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Ice Lake-LP DRAM, Memory: 16GB, Disk: Toshiba KBG40ZPZ512G NVMe 512GB, Graphics: Intel Iris Plus G7 3GB (1100MHz), Audio: Realtek ALC289, Network: Intel Killer Wi-Fi 6 AX1650i 160MHz OS: Ubuntu 20.10, Kernel: 5.9.0-050900-generic (x86_64), Desktop: GNOME Shell 3.38.2, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.2.6, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1200 2: Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Ice Lake-LP DRAM, Memory: 16GB, Disk: Toshiba KBG40ZPZ512G NVMe 512GB, Graphics: Intel Iris Plus G7 3GB (1100MHz), Audio: Realtek ALC289, Network: Intel Killer Wi-Fi 6 AX1650i 160MHz OS: Ubuntu 20.10, Kernel: 5.9.0-050900-generic (x86_64), Desktop: GNOME Shell 3.38.2, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.2.6, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1200 3: Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Ice Lake-LP DRAM, Memory: 16GB, Disk: Toshiba KBG40ZPZ512G NVMe 512GB, Graphics: Intel Iris Plus G7 3GB (1100MHz), Audio: Realtek ALC289, Network: Intel Killer Wi-Fi 6 AX1650i 160MHz OS: Ubuntu 20.10, Kernel: 5.9.0-050900-generic (x86_64), Desktop: GNOME Shell 3.38.2, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.2.6, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1200 oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 15.64736 |================================================================= 2 . 9.39567 |======================================= 3 . 9.62702 |======================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 9.31478 |================================================================== 2 . 8.04446 |========================================================= 3 . 8.03146 |========================================================= oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.78423 |================================================================== 2 . 3.45376 |============================================================ 3 . 3.24922 |========================================================= oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.41595 |================================================================== 2 . 4.14708 |============================================================== 3 . 4.16486 |============================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 36.96 |==================================================================== 2 . 34.43 |=============================================================== 3 . 34.41 |=============================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 12.27 |==================================================================== 2 . 11.54 |================================================================ 3 . 11.32 |=============================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 18.11 |==================================================================== 2 . 17.18 |================================================================= 3 . 16.47 |============================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 22.30 |================================================================== 2 . 22.06 |================================================================== 3 . 22.88 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 14.82 |================================================================ 2 . 14.99 |================================================================= 3 . 15.77 |==================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 12.57 |================================================================== 2 . 12.73 |=================================================================== 3 . 12.97 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.69711 |================================================================== 2 . 4.44703 |============================================================== 3 . 4.70558 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.04089 |================================================================ 2 . 3.85943 |============================================================= 3 . 4.18308 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 13325.6 |================================================================= 2 . 13255.0 |================================================================= 3 . 13492.6 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6709.12 |================================================================ 2 . 6842.26 |================================================================= 3 . 6944.84 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 12895.5 |=============================================================== 2 . 13254.3 |================================================================= 3 . 13425.8 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 68.46 |=============================================================== 2 . 72.60 |=================================================================== 3 . 73.39 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 83.70 |=============================================================== 2 . 89.81 |==================================================================== 3 . 90.29 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 54.33 |============================================================== 2 . 59.08 |==================================================================== 3 . 59.23 |==================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 6565.11 |============================================================== 2 . 6943.26 |================================================================== 3 . 6954.15 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 5.83056 |=========================================================== 2 . 6.38842 |================================================================= 3 . 6.50484 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 12670.4 |============================================================== 2 . 13341.8 |================================================================= 3 . 13445.0 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 6633.23 |=============================================================== 2 . 6939.88 |================================================================== 3 . 6934.93 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.36118 |=========================================================== 2 . 3.72900 |================================================================== 3 . 3.72438 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 16.62 |=============================================================== 2 . 17.75 |=================================================================== 3 . 17.94 |==================================================================== Sysbench 1.0.20 Test: RAM / Memory MiB/sec > Higher Is Better 1 . 15571.54 |================================================================= 2 . 14396.10 |============================================================ 3 . 14220.16 |=========================================================== Sysbench 1.0.20 Test: CPU Events Per Second > Higher Is Better 1 . 9839.21 |================================================================== 2 . 9311.07 |============================================================== 3 . 9326.28 |===============================================================