MKL-DNN DNNL Ice Lake
Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus 3GB on Ubuntu 19.10 via the Phoronix Test Suite.


Ice Lake: 

	Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Device 34ef, Memory: 16384MB, Disk: KBG40ZPZ512G NVMe TOSHIBA 512GB, Graphics: Intel Iris Plus 3GB (1100MHz), Audio: Realtek ALC289, Network: Intel Device 34f0

	OS: Ubuntu 19.10, Kernel: 5.3.0-19-generic (x86_64), Desktop: GNOME Shell 3.34.1, Display Server: X Server 1.20.5, Display Driver: modesetting 1.20.5, OpenGL: 4.6 Mesa 19.3.0-devel (git-1961653 2019-10-24 eoan-oibaf-ppa), Vulkan: 1.1.102, Compiler: GCC 9.2.1 20191008, File-System: ext4, Screen Resolution: 1920x1200


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_all - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 43628.27 |==========================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_all - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 27762.50 |==========================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_all - Data Type: f32
ms < Lower Is Better
Ice Lake . 10231.63 |==========================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_all - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 29589.37 |==========================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_all - Data Type: f32
ms < Lower Is Better
Ice Lake . 7212.46 |===========================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_3d - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 56201.73 |==========================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_googlenet_v3 - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 2000.19 |===========================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 32198.43 |==========================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 146.84 |============================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32
ms < Lower Is Better
Ice Lake . 571.21 |============================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_1d - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 69.87 |=============================================================


MKL-DNN DNNL 1.1
Harness: IP Batch 1D - Data Type: f32
ms < Lower Is Better
Ice Lake . 11.76 |=============================================================


MKL-DNN DNNL 1.1
Harness: IP Batch 1D - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 33.86 |=============================================================


MKL-DNN DNNL 1.1
Harness: IP Batch 1D - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 3.88 |==============================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 329.57 |============================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_alexnet - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 7964.69 |===========================================================


MKL-DNN DNNL 1.1
Harness: IP Batch All - Data Type: f32
ms < Lower Is Better
Ice Lake . 22.49 |=============================================================


MKL-DNN DNNL 1.1
Harness: IP Batch All - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 38.65 |=============================================================


MKL-DNN DNNL 1.1
Harness: IP Batch All - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 13.49 |=============================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_3d - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 163.08 |============================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_3d - Data Type: f32
ms < Lower Is Better
Ice Lake . 50.17 |=============================================================


MKL-DNN DNNL 1.1
Harness: Recurrent Neural Network Training - Data Type: f32
ms < Lower Is Better
Ice Lake . 827.94 |============================================================


MKL-DNN DNNL 1.1
Harness: Convolution Batch conv_alexnet - Data Type: f32
ms < Lower Is Better
Ice Lake . 1235.74 |===========================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32
ms < Lower Is Better
Ice Lake . 3.92 |==============================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_1d - Data Type: f32
ms < Lower Is Better
Ice Lake . 15.68 |=============================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_3d - Data Type: bf16bf16bf16
ms < Lower Is Better
Ice Lake . 50.24 |=============================================================


MKL-DNN DNNL 1.1
Harness: Deconvolution Batch deconv_3d - Data Type: f32
ms < Lower Is Better
Ice Lake . 13.64 |=============================================================