AMD Ryzen 5 4500U testing with a LENOVO LNVNB161216 (EECN20WW BIOS) and AMD Renoir 512MB 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 2203314-NE-NEW4500U446
new 4500U
AMD Ryzen 5 4500U testing with a LENOVO LNVNB161216 (EECN20WW BIOS) and AMD Renoir 512MB on Ubuntu 21.10 via the Phoronix Test Suite.
A:
Processor: AMD Ryzen 5 4500U @ 2.38GHz (6 Cores), Motherboard: LENOVO LNVNB161216 (EECN20WW BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 256GB SK hynix HFM256GDHTNI-87A0B, Graphics: AMD Renoir 512MB (1500/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Realtek RTL8822CE 802.11ac PCIe
OS: Ubuntu 21.10, Kernel: 5.16.0-051600rc8daily20220108-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.0-devel (git-9cb9101 2022-01-08 impish-oibaf-ppa) (LLVM 13.0.0 DRM 3.44), Vulkan: 1.2.199, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080
B:
Processor: AMD Ryzen 5 4500U @ 2.38GHz (6 Cores), Motherboard: LENOVO LNVNB161216 (EECN20WW BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 256GB SK hynix HFM256GDHTNI-87A0B, Graphics: AMD Renoir 512MB (1500/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Realtek RTL8822CE 802.11ac PCIe
OS: Ubuntu 21.10, Kernel: 5.16.0-051600rc8daily20220108-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.0-devel (git-9cb9101 2022-01-08 impish-oibaf-ppa) (LLVM 13.0.0 DRM 3.44), Vulkan: 1.2.199, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080
C:
Processor: AMD Ryzen 5 4500U @ 2.38GHz (6 Cores), Motherboard: LENOVO LNVNB161216 (EECN20WW BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 256GB SK hynix HFM256GDHTNI-87A0B, Graphics: AMD Renoir 512MB (1500/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Realtek RTL8822CE 802.11ac PCIe
OS: Ubuntu 21.10, Kernel: 5.16.0-051600rc8daily20220108-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.0-devel (git-9cb9101 2022-01-08 impish-oibaf-ppa) (LLVM 13.0.0 DRM 3.44), Vulkan: 1.2.199, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080
ONNX Runtime 1.11
Model: GPT-2 - Device: CPU - Executor: Parallel
Inferences Per Minute > Higher Is Better
A . 3438 |===================================================================
B . 3516 |=====================================================================
C . 3436 |===================================================================
ONNX Runtime 1.11
Model: GPT-2 - Device: CPU - Executor: Standard
Inferences Per Minute > Higher Is Better
A . 4018 |====================================================================
B . 4040 |=====================================================================
C . 4052 |=====================================================================
ONNX Runtime 1.11
Model: yolov4 - Device: CPU - Executor: Parallel
Inferences Per Minute > Higher Is Better
A . 162 |=====================================================================
B . 165 |======================================================================
C . 165 |======================================================================
ONNX Runtime 1.11
Model: yolov4 - Device: CPU - Executor: Standard
Inferences Per Minute > Higher Is Better
A . 173 |====================================================================
B . 178 |======================================================================
C . 172 |====================================================================
ONNX Runtime 1.11
Model: bertsquad-12 - Device: CPU - Executor: Parallel
Inferences Per Minute > Higher Is Better
A . 253 |=====================================================================
B . 258 |======================================================================
C . 257 |======================================================================
ONNX Runtime 1.11
Model: bertsquad-12 - Device: CPU - Executor: Standard
Inferences Per Minute > Higher Is Better
A . 299 |=====================================================================
B . 305 |======================================================================
C . 302 |=====================================================================
ONNX Runtime 1.11
Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel
Inferences Per Minute > Higher Is Better
A . 29 |=====================================================================
B . 30 |=======================================================================
C . 30 |=======================================================================
ONNX Runtime 1.11
Model: fcn-resnet101-11 - Device: CPU - Executor: Standard
Inferences Per Minute > Higher Is Better
A . 31 |=====================================================================
B . 32 |=======================================================================
C . 32 |=======================================================================
ONNX Runtime 1.11
Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel
Inferences Per Minute > Higher Is Better
A . 596 |======================================================================
B . 597 |======================================================================
C . 589 |=====================================================================
ONNX Runtime 1.11
Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard
Inferences Per Minute > Higher Is Better
A . 626 |=====================================================================
B . 634 |======================================================================
C . 629 |=====================================================================
ONNX Runtime 1.11
Model: super-resolution-10 - Device: CPU - Executor: Parallel
Inferences Per Minute > Higher Is Better
A . 1883 |===================================================================
B . 1928 |=====================================================================
C . 1931 |=====================================================================
ONNX Runtime 1.11
Model: super-resolution-10 - Device: CPU - Executor: Standard
Inferences Per Minute > Higher Is Better
A . 1959 |====================================================================
B . 1982 |=====================================================================
C . 1987 |=====================================================================
oneDNN 2.6
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 10.34 |===================================================================
B . 10.50 |====================================================================
C . 10.37 |===================================================================
oneDNN 2.6
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 11.50 |===================================================================
B . 11.68 |====================================================================
C . 11.57 |===================================================================
oneDNN 2.6
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 3.76309 |==================================================================
B . 3.60674 |===============================================================
C . 3.72157 |=================================================================
oneDNN 2.6
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 3.25725 |==============================================================
B . 3.42344 |==================================================================
C . 3.44368 |==================================================================
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 . 30.98 |===================================================================
B . 31.21 |====================================================================
C . 31.20 |====================================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 10.02906 |================================================================
B . 9.67935 |==============================================================
C . 10.19340 |=================================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 11.37 |============================================================
B . 12.86 |====================================================================
C . 12.67 |===================================================================
oneDNN 2.6
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 29.54 |====================================================================
B . 29.62 |====================================================================
C . 29.72 |====================================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 5.65617 |=================================================================
B . 5.53749 |================================================================
C . 5.70432 |==================================================================
oneDNN 2.6
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 7.34888 |===========================================================
B . 7.79921 |===============================================================
C . 8.19437 |==================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 7479.03 |================================================================
B . 7685.45 |==================================================================
C . 7452.65 |================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 4563.35 |==================================================================
B . 4483.24 |=================================================================
C . 4546.36 |==================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 7653.55 |==================================================================
B . 7485.04 |=================================================================
C . 7559.54 |=================================================================
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 . 4556.32 |==================================================================
B . 4465.22 |=================================================================
C . 4512.85 |=================================================================
oneDNN 2.6
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 6.11836 |=================================================================
B . 6.13719 |==================================================================
C . 6.16603 |==================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
A . 7602.29 |==================================================================
B . 7564.71 |==================================================================
C . 7536.09 |=================================================================
oneDNN 2.6
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
A . 4577.21 |==================================================================
B . 4586.79 |==================================================================
C . 4526.15 |=================================================================
oneDNN 2.6
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 4.45587 |==================================================================
B . 4.47616 |==================================================================
C . 4.48426 |==================================================================
oneDNN 2.6
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better