Cascade 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.


skylake-avx512: 

	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 9.0.1 20190414, File-System: ext4, Screen Resolution: 1920x1080

cascadelake: 

	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 9.0.1 20190414, File-System: ext4, Screen Resolution: 1920x1080


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_3d - Data Type: f32
ms < Lower Is Better
skylake-avx512 . 4.99 |========================================================
cascadelake .... 4.37 |=================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_all - Data Type: f32
ms < Lower Is Better
skylake-avx512 . 393 |=========================================================
cascadelake .... 390 |=========================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_1d - Data Type: f32
ms < Lower Is Better
skylake-avx512 . 1.36 |========================================================
cascadelake .... 1.24 |===================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_3d - Data Type: f32
ms < Lower Is Better
skylake-avx512 . 2.50 |========================================================
cascadelake .... 2.32 |====================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_alexnet - Data Type: f32
ms < Lower Is Better
skylake-avx512 . 55.35 |=======================================================
cascadelake .... 52.16 |====================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_all - Data Type: f32
ms < Lower Is Better
skylake-avx512 . 836 |=========================================================
cascadelake .... 826 |========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_3d - Data Type: u8s8u8s32
ms < Lower Is Better
skylake-avx512 . 4.48 |========================================================
cascadelake .... 4.45 |========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_all - Data Type: u8s8u8s32
ms < Lower Is Better
skylake-avx512 . 389 |=========================================================
cascadelake .... 391 |=========================================================


MKL-DNN 2019-04-16
Harness: Deconvolution Batch deconv_1d - Data Type: u8s8u8s32
ms < Lower Is Better
skylake-avx512 . 1.31 |========================================================
cascadelake .... 1.32 |========================================================


MKL-DNN 2019-04-16
Harness: Convolution Batch conv_alexnet - Data Type: u8s8u8s32
ms < Lower Is Better
skylake-avx512 . 56.08 |=======================================================
cascadelake .... 55.11 |======================================================