mnn 0905
2 x Hygon C86 7280 32-core testing with a Suma R6240H0 62DB32 v24002826 (CXYH051031 BIOS) and ASPEED on Ubuntu 24.04 via the Phoronix Test Suite.


2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0: 

	Processor: 2 x Hygon C86 7280 32-core (64 Cores / 128 Threads), Motherboard: Suma R6240H0 62DB32 v24002826 (CXYH051031 BIOS), Chipset: Chengdu Haiguang IC Design Root Complex, Memory: 1008GB, Disk: 256GB MR9361-8i + 1920GB MR9361-8i + 12001GB MR9361-8i, Graphics: ASPEED, Network: 2 x Intel I350 + 4 x Mellanox MT27710

	OS: Ubuntu 24.04, Kernel: 6.8.0-41-generic (x86_64), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1024x768


Mobile Neural Network 2.9.b11b7037d
Model: inception-v3
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 78.09 |===================


Mobile Neural Network 2.9.b11b7037d
Model: mobilenet-v1-1.0
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 8.855 |===================


Mobile Neural Network 2.9.b11b7037d
Model: MobileNetV2_224
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 14.22 |===================


Mobile Neural Network 2.9.b11b7037d
Model: SqueezeNetV1.0
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 19.72 |===================


Mobile Neural Network 2.9.b11b7037d
Model: resnet-v2-50
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 73.06 |===================


Mobile Neural Network 2.9.b11b7037d
Model: squeezenetv1.1
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 13.11 |===================


Mobile Neural Network 2.9.b11b7037d
Model: mobilenetV3
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 6.812 |===================


Mobile Neural Network 2.9.b11b7037d
Model: nasnet
ms < Lower Is Better
2 x Hygon C86 7280 32-core - ASPEED - Suma R6240H0 . 54.22 |===================