i9 10980XE oneDNN
Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.30 BIOS) and NVIDIA NV132 11GB on Ubuntu 20.04 via the Phoronix Test Suite.


Core i9 10980XE: 

	Processor: Intel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads), Motherboard: ASRock X299 Steel Legend (P1.30 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 32GB, Disk: Samsung SSD 970 PRO 512GB, Graphics: NVIDIA NV132 11GB, Audio: Realtek ALC1220, Monitor: DELL P2415Q, Network: Intel I219-V + Intel I211

	OS: Ubuntu 20.04, Kernel: 5.4.0-31-generic (x86_64), Desktop: GNOME Shell 3.36.1, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.3 Mesa 20.0.4, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160


Zstd Compression 1.4.5
Compression Level: 3
MB/s > Higher Is Better
Core i9 10980XE . 4732.4 |=====================================================


Zstd Compression 1.4.5
Compression Level: 19
MB/s > Higher Is Better
Core i9 10980XE . 60.2 |=======================================================


oneDNN 1.5
Harness: IP Batch 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 5.81494 |====================================================


oneDNN 1.5
Harness: IP Batch All - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 33.63 |======================================================


oneDNN 1.5
Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 0.520544 |===================================================


oneDNN 1.5
Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 7.39512 |====================================================


oneDNN 1.5
Harness: IP Batch 1D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 5.59420 |====================================================


oneDNN 1.5
Harness: IP Batch All - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 64.15 |======================================================


oneDNN 1.5
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 9.82147 |====================================================


oneDNN 1.5
Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 1.73847 |====================================================


oneDNN 1.5
Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 2.67626 |====================================================


oneDNN 1.5
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 9.29002 |====================================================


oneDNN 1.5
Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 0.462452 |===================================================


oneDNN 1.5
Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 0.696851 |===================================================


oneDNN 1.5
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 168.49 |=====================================================


oneDNN 1.5
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 53.81 |======================================================


oneDNN 1.5
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 8.07568 |====================================================


oneDNN 1.5
Harness: Deconvolution Batch deconv_1d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 9.29792 |====================================================


oneDNN 1.5
Harness: Deconvolution Batch deconv_3d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 10.89 |======================================================


oneDNN 1.5
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 1.41428 |====================================================


oneDNN 1.5
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 0.366970 |===================================================


oneDNN 1.5
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Core i9 10980XE . 1.72197 |====================================================


WireGuard + Linux Networking Stack Stress Test

Seconds < Lower Is Better
Core i9 10980XE . 242.35 |=====================================================