mnn grace
ARMv8 Neoverse-V2 testing with a Pegatron JIMBO P4352 (00022432 BIOS) and ASPEED on Ubuntu 24.04 via the Phoronix Test Suite.


a: 

	Processor: ARMv8 Neoverse-V2 @ 3.47GHz (72 Cores), Motherboard: Pegatron JIMBO P4352 (00022432 BIOS), Memory: 1 x 480GB LPDDR5-6400MT/s NVIDIA 699-2G530-0236-RC1, Disk: 1000GB CT1000T700SSD3, Graphics: ASPEED, Network: 2 x Intel X550

	OS: Ubuntu 24.04, Kernel: 6.8.0-48-generic-64k (aarch64), Compiler: GCC 13.2.0 + Clang 18.1.3 + CUDA 11.8, File-System: ext4, Screen Resolution: 1920x1200

b: 

	Processor: ARMv8 Neoverse-V2 @ 3.47GHz (72 Cores), Motherboard: Pegatron JIMBO P4352 (00022432 BIOS), Memory: 1 x 480GB LPDDR5-6400MT/s NVIDIA 699-2G530-0236-RC1, Disk: 1000GB CT1000T700SSD3, Graphics: ASPEED, Network: 2 x Intel X550

	OS: Ubuntu 24.04, Kernel: 6.8.0-48-generic-64k (aarch64), Compiler: GCC 13.2.0 + Clang 18.1.3 + CUDA 11.8, File-System: ext4, Screen Resolution: 1920x1200

c: 

	Processor: ARMv8 Neoverse-V2 @ 3.47GHz (72 Cores), Motherboard: Pegatron JIMBO P4352 (00022432 BIOS), Memory: 1 x 480GB LPDDR5-6400MT/s NVIDIA 699-2G530-0236-RC1, Disk: 1000GB CT1000T700SSD3, Graphics: ASPEED, Network: 2 x Intel X550

	OS: Ubuntu 24.04, Kernel: 6.8.0-48-generic-64k (aarch64), Compiler: GCC 13.2.0 + Clang 18.1.3 + CUDA 11.8, File-System: ext4, Screen Resolution: 1920x1200

d: 

	Processor: ARMv8 Neoverse-V2 @ 3.47GHz (72 Cores), Motherboard: Pegatron JIMBO P4352 (00022432 BIOS), Memory: 1 x 480GB LPDDR5-6400MT/s NVIDIA 699-2G530-0236-RC1, Disk: 1000GB CT1000T700SSD3, Graphics: ASPEED, Network: 2 x Intel X550

	OS: Ubuntu 24.04, Kernel: 6.8.0-48-generic-64k (aarch64), Compiler: GCC 13.2.0 + Clang 18.1.3 + CUDA 11.8, File-System: ext4, Screen Resolution: 1920x1200


Mobile Neural Network 3.0
Model: inception-v3
ms < Lower Is Better
a . 7.665 |====================================================================
b . 7.705 |====================================================================
c . 7.683 |====================================================================
d . 7.700 |====================================================================


Mobile Neural Network 3.0
Model: mobilenet-v1-1.0
ms < Lower Is Better
a . 1.056 |====================================================================
b . 1.052 |====================================================================
c . 1.053 |====================================================================
d . 1.047 |===================================================================


Mobile Neural Network 3.0
Model: MobileNetV2_224
ms < Lower Is Better
a . 1.016 |====================================================================
b . 1.005 |===================================================================
c . 1.017 |====================================================================
d . 1.013 |====================================================================


Mobile Neural Network 3.0
Model: SqueezeNetV1.0
ms < Lower Is Better
a . 1.782 |====================================================================
b . 1.792 |====================================================================
c . 1.763 |===================================================================
d . 1.785 |====================================================================


Mobile Neural Network 3.0
Model: resnet-v2-50
ms < Lower Is Better
a . 6.149 |====================================================================
b . 6.071 |===================================================================
c . 6.028 |==================================================================
d . 6.177 |====================================================================


Mobile Neural Network 3.0
Model: squeezenetv1.1
ms < Lower Is Better
a . 0.979 |===================================================================
b . 0.976 |===================================================================
c . 0.974 |===================================================================
d . 0.989 |====================================================================


Mobile Neural Network 3.0
Model: mobilenetV3
ms < Lower Is Better
a . 0.864 |==================================================================
b . 0.876 |===================================================================
c . 0.877 |===================================================================
d . 0.887 |====================================================================


Mobile Neural Network 3.0
Model: nasnet
ms < Lower Is Better
a . 3.969 |====================================================================
b . 3.990 |====================================================================
c . 3.993 |====================================================================
d . 3.962 |===================================================================