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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2103134-HA-SYSBENCHO81
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
Sysbench 1.0.20
Test: CPU
Events Per Second > Higher Is Better
1 . 9839.21 |==================================================================
2 . 9311.07 |==============================================================
3 . 9326.28 |===============================================================
Sysbench 1.0.20
Test: RAM / Memory
MiB/sec > Higher Is Better
1 . 15571.54 |=================================================================
2 . 14396.10 |============================================================
3 . 14220.16 |===========================================================
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 |====================================================================