minervatensorflowNOHT
2 x Intel Xeon Silver 4314 testing with a Intel M20NTP2SB (SE5C620.86B.0021.D02.2204261106 BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.


minerva sin HT: 

	Processor: 2 x Intel Xeon Silver 4314 @ 3.40GHz (32 Cores), Motherboard: Intel M20NTP2SB (SE5C620.86B.0021.D02.2204261106 BIOS), Chipset: Intel Device 0998, Memory: 128GB, Disk: 2 x 1920GB KINGSTON SEDC1500M1920G + 2 x 6001GB Western Digital WD6003FFBX-6, Graphics: ASPEED, Monitor: Smart Cable, Network: 2 x Intel I210

	OS: Ubuntu 22.04, Kernel: 5.15.0-71-generic (x86_64), Vulkan: 1.3.224, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1024x768


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: VGG-16
images/sec > Higher Is Better
minerva sin HT . 14.70 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: VGG-16
images/sec > Higher Is Better
minerva sin HT . 16.97 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: VGG-16
images/sec > Higher Is Better
minerva sin HT . 18.95 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
minerva sin HT . 143.93 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: VGG-16
images/sec > Higher Is Better
minerva sin HT . 20.69 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: AlexNet
images/sec > Higher Is Better
minerva sin HT . 206.65 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: VGG-16
images/sec > Higher Is Better
minerva sin HT . 20.85 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: AlexNet
images/sec > Higher Is Better
minerva sin HT . 250.10 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: AlexNet
images/sec > Higher Is Better
minerva sin HT . 357.11 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: AlexNet
images/sec > Higher Is Better
minerva sin HT . 407.59 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
minerva sin HT . 95.37 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
minerva sin HT . 26.07 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: GoogLeNet
images/sec > Higher Is Better
minerva sin HT . 98.96 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: ResNet-50
images/sec > Higher Is Better
minerva sin HT . 28.40 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: GoogLeNet
images/sec > Higher Is Better
minerva sin HT . 105.67 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: ResNet-50
images/sec > Higher Is Better
minerva sin HT . 30.71 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: GoogLeNet
images/sec > Higher Is Better
minerva sin HT . 118.02 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: ResNet-50
images/sec > Higher Is Better
minerva sin HT . 33.04 |=======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: GoogLeNet
images/sec > Higher Is Better
minerva sin HT . 116.42 |======================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: ResNet-50
images/sec > Higher Is Better
minerva sin HT . 33.91 |=======================================================