AMD Ryzen 5 5500U testing with a LENOVO LNVNB161216 (GLCN22WW BIOS) and AMD Lucienne 2GB on Ubuntu 21.10 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 2203306-PTS-ONEDNN5567
onednn 5500U
AMD Ryzen 5 5500U testing with a LENOVO LNVNB161216 (GLCN22WW BIOS) and AMD Lucienne 2GB on Ubuntu 21.10 via the Phoronix Test Suite.
A:
Processor: AMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads), Motherboard: LENOVO LNVNB161216 (GLCN22WW BIOS), Chipset: AMD Renoir/Cezanne, Memory: 6GB, Disk: 256GB SAMSUNG MZALQ256HBJD-00BL2, Graphics: AMD Lucienne 2GB (1800/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Qualcomm Atheros QCA6174 802.11ac
OS: Ubuntu 21.10, Kernel: 5.17.0-051700-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server 1.20.13 + Wayland, OpenGL: 4.6 Mesa 22.1.0-devel (git-729f95a 2022-03-24 impish-oibaf-ppa) (LLVM 13.0.1 DRM 3.44), Vulkan: 1.3.207, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080
B:
Processor: AMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads), Motherboard: LENOVO LNVNB161216 (GLCN22WW BIOS), Chipset: AMD Renoir/Cezanne, Memory: 6GB, Disk: 256GB SAMSUNG MZALQ256HBJD-00BL2, Graphics: AMD Lucienne 2GB (1800/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Qualcomm Atheros QCA6174 802.11ac
OS: Ubuntu 21.10, Kernel: 5.17.0-051700-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server 1.20.13 + Wayland, OpenGL: 4.6 Mesa 22.1.0-devel (git-729f95a 2022-03-24 impish-oibaf-ppa) (LLVM 13.0.1 DRM 3.44), Vulkan: 1.3.207, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080
C:
Processor: AMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads), Motherboard: LENOVO LNVNB161216 (GLCN22WW BIOS), Chipset: AMD Renoir/Cezanne, Memory: 6GB, Disk: 256GB SAMSUNG MZALQ256HBJD-00BL2, Graphics: AMD Lucienne 2GB (1800/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Qualcomm Atheros QCA6174 802.11ac
OS: Ubuntu 21.10, Kernel: 5.17.0-051700-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server 1.20.13 + Wayland, OpenGL: 4.6 Mesa 22.1.0-devel (git-729f95a 2022-03-24 impish-oibaf-ppa) (LLVM 13.0.1 DRM 3.44), Vulkan: 1.3.207, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080
oneDNN 2.6
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 12.11 |====================================================================
B . 12.09 |====================================================================
C . 12.09 |====================================================================
oneDNN 2.6
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 14.50 |====================================================================
B . 11.33 |=====================================================
C . 11.39 |=====================================================
oneDNN 2.6
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 3.72999 |=================================================================
B . 3.79690 |==================================================================
C . 3.79445 |==================================================================
oneDNN 2.6
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 4.55304 |==================================================================
B . 3.75469 |======================================================
C . 3.76327 |=======================================================
oneDNN 2.6
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.6
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.6
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 34.45 |====================================================================
B . 34.12 |===================================================================
C . 34.16 |===================================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 13.62 |====================================================================
B . 13.64 |====================================================================
C . 13.33 |==================================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 11.76 |====================================================================
B . 11.72 |====================================================================
C . 11.72 |====================================================================
oneDNN 2.6
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 37.77 |====================================================================
B . 33.74 |=============================================================
C . 33.72 |=============================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 5.62842 |=================================================================
B . 5.61911 |=================================================================
C . 5.70647 |==================================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 8.03215 |==================================================================
B . 8.02814 |==================================================================
C . 8.03124 |==================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 7127.16 |==================================================================
B . 7087.03 |==================================================================
C . 7043.60 |=================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 4688.21 |==================================================================
B . 4690.55 |==================================================================
C . 4690.50 |==================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 7099.28 |==================================================================
B . 7098.27 |==================================================================
C . 7066.77 |==================================================================
oneDNN 2.6
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.6
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.6
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.6
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 4694.72 |==================================================================
B . 4701.50 |==================================================================
C . 4676.62 |==================================================================
oneDNN 2.6
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 7.90632 |==================================================================
B . 7.89074 |==================================================================
C . 7.85276 |==================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
A . 7073.68 |==================================================================
B . 7067.16 |==================================================================
C . 7094.51 |==================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
A . 4687.06 |==================================================================
B . 4683.43 |==================================================================
C . 4662.02 |==================================================================
oneDNN 2.6
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 5.11790 |==================================================================
B . 5.11311 |==================================================================
C . 5.11709 |==================================================================
oneDNN 2.6
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better