Cascadelake MKL-DNN
2 x Intel Xeon Platinum 8280 testing with a GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS) and ASPEED Family on Ubuntu 18.04 via the Phoronix Test Suite.


2 x 8280: 

	Processor: 2 x Intel Xeon Platinum 8280 @ 4.00GHz (56 Cores / 112 Threads), Motherboard: GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 386048MB, Disk: Samsung SSD 970 PRO 512GB, Graphics: ASPEED Family, Monitor: VE228, Network: 2 x Intel X722 for 1GbE + 2 x QLogic FastLinQ QL41000 10/25/40/50GbE

	OS: Ubuntu 18.04, Kernel: 5.1.0-999-generic (x86_64) 20190416, Desktop: GNOME Shell 3.28.3, Display Server: X Server 1.20.1, Display Driver: modesetting 1.20.1, Compiler: GCC 7.3.0, File-System: ext4, Screen Resolution: 1920x1080


MKL-DNN 2019-04-16
Harness: IP Batch 1D - Data Type: f32
ms < Lower Is Better
2 x 8280 . 11.65 |=============================================================


MKL-DNN 2019-04-16
Harness: IP Batch All - Data Type: f32
ms < Lower Is Better
2 x 8280 . 101.17 |============================================================


MKL-DNN 2019-04-16
Harness: IP Batch 1D - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 3.54 |==============================================================


MKL-DNN 2019-04-16
Harness: IP Batch 1D - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 3.63 |==============================================================


MKL-DNN 2019-04-16
Harness: IP Batch All - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 20.45 |=============================================================


MKL-DNN 2019-04-16
Harness: IP Batch All - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 20.38 |=============================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_3d - Data Type: f32
ms < Lower Is Better
2 x 8280 . 3.29 |==============================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_all - Data Type: f32
ms < Lower Is Better
2 x 8280 . 382 |===============================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_1d - Data Type: f32
ms < Lower Is Better
2 x 8280 . 0.95 |==============================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_3d - Data Type: f32
ms < Lower Is Better
2 x 8280 . 1.10 |==============================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_alexnet - Data Type: f32
ms < Lower Is Better
2 x 8280 . 48.42 |=============================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_all - Data Type: f32
ms < Lower Is Better
2 x 8280 . 984 |===============================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_3d - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 2607.67 |===========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_3d - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 2633.71 |===========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_all - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 1260 |==============================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_all - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 1300.71 |===========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32
ms < Lower Is Better
2 x 8280 . 21.13 |=============================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_1d - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 0.23 |==============================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_3d - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 2256.19 |===========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_alexnet - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 14.06 |=============================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 0.23 |==============================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 2181.05 |===========================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_all - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 3982.35 |===========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 19.24 |=============================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8u8s32
ms < Lower Is Better
2 x 8280 . 5.71 |==============================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32s32
ms < Lower Is Better
2 x 8280 . 6.16 |==============================================================