threadripper tensorflow 2.16
AMD Ryzen Threadripper 7980X 64-Cores testing with a System76 Thelio Major (FA Z5 BIOS) and AMD Radeon Pro W7900 45GB on Ubuntu 23.10 via the Phoronix Test Suite.


a: 

	Processor: AMD Ryzen Threadripper 7980X 64-Cores @ 7.79GHz (64 Cores / 128 Threads), Motherboard: System76 Thelio Major (FA Z5 BIOS), Chipset: AMD Device 14a4, Memory: 4 x 32GB DRAM-4800MT/s Micron MTC20F1045S1RC48BA2, Disk: 1000GB CT1000T700SSD5, Graphics: AMD Radeon Pro W7900 45GB (1760/1124MHz), Audio: AMD Device 14cc, Monitor: DELL P2415Q, Network: Aquantia AQC113C NBase-T/IEEE + Realtek RTL8125 2.5GbE + Intel Wi-Fi 6 AX210/AX211/AX411

	OS: Ubuntu 23.10, Kernel: 6.5.0-26-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.2.1-1ubuntu3.1 (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1080

b: 

	Processor: AMD Ryzen Threadripper 7980X 64-Cores @ 7.79GHz (64 Cores / 128 Threads), Motherboard: System76 Thelio Major (FA Z5 BIOS), Chipset: AMD Device 14a4, Memory: 4 x 32GB DRAM-4800MT/s Micron MTC20F1045S1RC48BA2, Disk: 1000GB CT1000T700SSD5, Graphics: AMD Radeon Pro W7900 45GB (1760/1124MHz), Audio: AMD Device 14cc, Monitor: DELL P2415Q, Network: Aquantia AQC113C NBase-T/IEEE + Realtek RTL8125 2.5GbE + Intel Wi-Fi 6 AX210/AX211/AX411

	OS: Ubuntu 23.10, Kernel: 6.5.0-26-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.2.1-1ubuntu3.1 (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1080


TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: AlexNet
images/sec > Higher Is Better
a . 26.79 |====================================================================
b . 26.52 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
a . 329.01 |===================================================================
b . 330.15 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: AlexNet
images/sec > Higher Is Better
a . 539.47 |===================================================================
b . 536.96 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: AlexNet
images/sec > Higher Is Better
a . 775.80 |===================================================================
b . 777.02 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: GoogLeNet
images/sec > Higher Is Better
a . 48.22 |====================================================================
b . 48.29 |====================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
images/sec > Higher Is Better
a . 13.23 |=================================================================
b . 13.82 |====================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 256 - Model: AlexNet
images/sec > Higher Is Better
a . 1125.50 |==================================================================
b . 1124.79 |==================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 512 - Model: AlexNet
images/sec > Higher Is Better
a . 1181.85 |==================================================================
b . 1181.57 |==================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
a . 214.12 |===================================================================
b . 214.13 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
a . 63.34 |====================================================================
b . 63.03 |====================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: GoogLeNet
images/sec > Higher Is Better
a . 246.23 |===================================================================
b . 244.36 |==================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: ResNet-50
images/sec > Higher Is Better
a . 73.70 |====================================================================
b . 73.27 |====================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: GoogLeNet
images/sec > Higher Is Better
a . 278.45 |===================================================================
b . 278.59 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: ResNet-50
images/sec > Higher Is Better
a . 81.22 |====================================================================
b . 81.27 |====================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 256 - Model: GoogLeNet
images/sec > Higher Is Better
a . 304.84 |===================================================================
b . 305.01 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 256 - Model: ResNet-50
images/sec > Higher Is Better
a . 86.27 |====================================================================
b . 85.99 |====================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 512 - Model: GoogLeNet
images/sec > Higher Is Better
a . 290.62 |===================================================================
b . 286.81 |==================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 512 - Model: ResNet-50
images/sec > Higher Is Better
a . 82.17 |====================================================================
b . 81.50 |===================================================================