epyc siena

Tests for a future article. AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2403268-NE-EPYCSIENA58
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
a
March 26
  1 Hour, 20 Minutes
b
March 26
  49 Minutes
Invert Hiding All Results Option
  1 Hour, 4 Minutes
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):

epyc siena Tests for a future article. AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite. ,,"a","b" Processor,,AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads),AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads) Motherboard,,AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS) Chipset,,AMD Device 14a4,AMD Device 14a4 Memory,,6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG Disk,,3201GB Micron_7450_MTFDKCB3T2TFS + 2000GB Corsair MP700,3201GB Micron_7450_MTFDKCB3T2TFS + 2000GB Corsair MP700 Graphics,,ASPEED,ASPEED Network,,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe OS,,Ubuntu 23.10,Ubuntu 23.10 Kernel,,6.8.1-060801-generic (x86_64),6.8.1-060801-generic (x86_64) Desktop,,GNOME Shell 45.2,GNOME Shell 45.2 Display Server,,X Server 1.21.1.7,X Server 1.21.1.7 Compiler,,GCC 13.2.0,GCC 13.2.0 File-System,,ext4,ext4 Screen Resolution,,1920x1200,1920x1200 ,,"a","b" "TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,35.28,37.82 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,64.29,63.55 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,26.08,25.82 "TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,79.54,78.85 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,32.96,32.71 "TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,10.9,10.98 "TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,285.85,284.4 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,349.15,347.83 "TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,89.84,89.51 "TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,11.40,11.43 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,64.85,64.68 "TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,249.12,249.77 "TensorFlow - Device: CPU - Batch Size: 32 - Model: VGG-16 (images/sec)",HIB,42.82,42.93 "TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,926.49,924.61 "TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec)",HIB,101.92,101.73 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,81.13,80.98 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,199.74,200.1 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,230.13,229.77 "TensorFlow - Device: CPU - Batch Size: 256 - Model: VGG-16 (images/sec)",HIB,45.78,45.71 "TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,34.38,34.43 "TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,529.36,530.09 "TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,704.03,703.08 "TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,887.98,889.09 "TensorFlow - Device: CPU - Batch Size: 512 - Model: ResNet-50 (images/sec)",HIB,104.53,104.61 "TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,39.78,39.79 "TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,320.31,320.23 "TensorFlow - Device: CPU - Batch Size: 64 - Model: VGG-16 (images/sec)",HIB,44.69,44.7 "TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec)",HIB,326.63,326.6 "Blender - Blend File: Junkshop - Compute: CPU-Only (sec)",LIB,34.32,34.32