MinervaTensorFlow
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.


MinervaTFRunAbril: 

	Processor: 2 x Intel Xeon Silver 4314 @ 3.40GHz (32 Cores / 64 Threads), 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: 5.15.0-70-generic (x86_64), Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1024x768


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: ResNet-50
images/sec > Higher Is Better
MinervaTFRunAbril . 25.82 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: GoogLeNet
images/sec > Higher Is Better
MinervaTFRunAbril . 101.69 |===================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: ResNet-50
images/sec > Higher Is Better
MinervaTFRunAbril . 25.44 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: GoogLeNet
images/sec > Higher Is Better
MinervaTFRunAbril . 99.24 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: ResNet-50
images/sec > Higher Is Better
MinervaTFRunAbril . 20.50 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: GoogLeNet
images/sec > Higher Is Better
MinervaTFRunAbril . 78.05 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: ResNet-50
images/sec > Higher Is Better
MinervaTFRunAbril . 17.38 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: GoogLeNet
images/sec > Higher Is Better
MinervaTFRunAbril . 62.15 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
MinervaTFRunAbril . 14.57 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
MinervaTFRunAbril . 49.97 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: AlexNet
images/sec > Higher Is Better
MinervaTFRunAbril . 259.35 |===================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: AlexNet
images/sec > Higher Is Better
MinervaTFRunAbril . 230.57 |===================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: AlexNet
images/sec > Higher Is Better
MinervaTFRunAbril . 147.59 |===================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: VGG-16
images/sec > Higher Is Better
MinervaTFRunAbril . 18.08 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: AlexNet
images/sec > Higher Is Better
MinervaTFRunAbril . 118.45 |===================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: VGG-16
images/sec > Higher Is Better
MinervaTFRunAbril . 15.87 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
MinervaTFRunAbril . 97.03 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: VGG-16
images/sec > Higher Is Better
MinervaTFRunAbril . 12.72 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: VGG-16
images/sec > Higher Is Better
MinervaTFRunAbril . 11.49 |====================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: VGG-16
images/sec > Higher Is Better
MinervaTFRunAbril . 9.94 |=====================================================