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AMD Ryzen 7 7840U testing with a Framework FRANMDCP07 (03.03 BIOS) and AMD Phoenix1 512MB on Ubuntu 23.10 via the Phoronix Test Suite.


a: 

	Processor: AMD Ryzen 7 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: Framework FRANMDCP07 (03.03 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 512GB Western Digital WD PC SN740 SDDPNQD-512G, Graphics: AMD Phoenix1 512MB (2700/2800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI

	OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2312160600.5d937f~oibaf~m (git-5d937f0 2023-12-16 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.56), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2256x1504

b: 

	Processor: AMD Ryzen 7 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: Framework FRANMDCP07 (03.03 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 512GB Western Digital WD PC SN740 SDDPNQD-512G, Graphics: AMD Phoenix1 512MB (2700/2800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI

	OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2312160600.5d937f~oibaf~m (git-5d937f0 2023-12-16 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.56), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2256x1504

c: 

	Processor: AMD Ryzen 7 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: Framework FRANMDCP07 (03.03 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 512GB Western Digital WD PC SN740 SDDPNQD-512G, Graphics: AMD Phoenix1 512MB (2700/2800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI

	OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2312160600.5d937f~oibaf~m (git-5d937f0 2023-12-16 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.56), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2256x1504


Quicksilver 20230818
Input: CTS2
Figure Of Merit > Higher Is Better
a . 10580000 |===============================================================
b . 10910000 |=================================================================
c . 10510000 |===============================================================


Quicksilver 20230818
Input: CORAL2 P1
Figure Of Merit > Higher Is Better
a . 11580000 |=================================================================
b . 11610000 |=================================================================
c . 11500000 |================================================================


Quicksilver 20230818
Input: CORAL2 P2
Figure Of Merit > Higher Is Better
a . 21860000 |=================================================================
b . 21860000 |=================================================================
c . 20910000 |==============================================================


Y-Cruncher 0.8.3
Pi Digits To Calculate: 1B
Seconds < Lower Is Better
a . 37.13 |===================================================================
b . 37.21 |===================================================================
c . 37.51 |====================================================================


Y-Cruncher 0.8.3
Pi Digits To Calculate: 500M
Seconds < Lower Is Better
a . 16.75 |====================================================================
b . 16.70 |====================================================================
c . 16.69 |====================================================================


PyTorch 2.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
a . 49.42 |===================================================================
b . 47.70 |=================================================================
c . 50.00 |====================================================================


PyTorch 2.1
Device: CPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
a . 20.10 |====================================================================
b . 19.93 |===================================================================
c . 19.75 |===================================================================


PyTorch 2.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
a . 28.64 |==================================================================
b . 27.86 |================================================================
c . 29.46 |====================================================================


PyTorch 2.1
Device: CPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
a . 12.50 |====================================================================
b . 12.37 |===================================================================
c . 12.50 |====================================================================


PyTorch 2.1
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 11.95 |====================================================================
b . 11.88 |====================================================================
c . 11.93 |====================================================================


PyTorch 2.1
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 8.52 |=====================================================================
b . 8.48 |=====================================================================
c . 8.40 |====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: VGG-16
images/sec > Higher Is Better
a . 3.42 |=====================================================================
b . 3.42 |=====================================================================
c . 3.41 |=====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: AlexNet
images/sec > Higher Is Better
a . 11.09 |====================================================================
b . 11.11 |====================================================================
c . 11.09 |====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: VGG-16
images/sec > Higher Is Better
a . 7.46 |=====================================================================
b . 7.46 |=====================================================================
c . 7.47 |=====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
a . 89.66 |====================================================================
b . 88.85 |===================================================================
c . 89.39 |====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: GoogLeNet
images/sec > Higher Is Better
a . 42.37 |====================================================================
b . 41.59 |===================================================================
c . 42.30 |====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: ResNet-50
images/sec > Higher Is Better
a . 11.35 |===================================================================
b . 11.38 |====================================================================
c . 11.46 |====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
a . 65.04 |===================================================================
b . 65.09 |====================================================================
c . 65.56 |====================================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
a . 21.85 |====================================================================
b . 21.84 |====================================================================
c . 21.84 |====================================================================