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

March 26

1 Hour, 20 Minutes

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: Processor: AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads), Motherboard: AMD Cinnabar (RCB1009C BIOS), Chipset: AMD Device 14a4, Memory: 6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG, Disk: 3201GB Micron_7450_MTFDKCB3T2TFS + 2000GB Corsair MP700, Graphics: ASPEED, Network: 2 x Broadcom NetXtreme BCM5720 PCIe OS: Ubuntu 23.10, Kernel: 6.8.1-060801-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 b: Processor: AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads), Motherboard: AMD Cinnabar (RCB1009C BIOS), Chipset: AMD Device 14a4, Memory: 6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG, Disk: 3201GB Micron_7450_MTFDKCB3T2TFS + 2000GB Corsair MP700, Graphics: ASPEED, Network: 2 x Broadcom NetXtreme BCM5720 PCIe OS: Ubuntu 23.10, Kernel: 6.8.1-060801-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 35.28 |=============================================================== b . 37.82 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 64.29 |==================================================================== b . 63.55 |=================================================================== Blender 4.1 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 26.08 |==================================================================== b . 25.82 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 images/sec > Higher Is Better a . 79.54 |==================================================================== b . 78.85 |=================================================================== Blender 4.1 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 32.96 |==================================================================== b . 32.71 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 10.90 |==================================================================== b . 10.98 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: GoogLeNet images/sec > Higher Is Better a . 285.85 |=================================================================== b . 284.40 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better a . 349.15 |=================================================================== b . 347.83 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 images/sec > Higher Is Better a . 89.84 |==================================================================== b . 89.51 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: VGG-16 images/sec > Higher Is Better a . 11.40 |==================================================================== b . 11.43 |==================================================================== Blender 4.1 Blend File: Classroom - Compute: CPU-Only Seconds < Lower Is Better a . 64.85 |==================================================================== b . 64.68 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: GoogLeNet images/sec > Higher Is Better a . 249.12 |=================================================================== b . 249.77 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: VGG-16 images/sec > Higher Is Better a . 42.82 |==================================================================== b . 42.93 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 512 - Model: AlexNet images/sec > Higher Is Better a . 926.49 |=================================================================== b . 924.61 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 images/sec > Higher Is Better a . 101.92 |=================================================================== b . 101.73 |=================================================================== Blender 4.1 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 81.13 |==================================================================== b . 80.98 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 199.74 |=================================================================== b . 200.10 |=================================================================== Blender 4.1 Blend File: Barbershop - Compute: CPU-Only Seconds < Lower Is Better a . 230.13 |=================================================================== b . 229.77 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: VGG-16 images/sec > Higher Is Better a . 45.78 |==================================================================== b . 45.71 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: AlexNet images/sec > Higher Is Better a . 34.38 |==================================================================== b . 34.43 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: AlexNet images/sec > Higher Is Better a . 529.36 |=================================================================== b . 530.09 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: AlexNet images/sec > Higher Is Better a . 704.03 |=================================================================== b . 703.08 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: AlexNet images/sec > Higher Is Better a . 887.98 |=================================================================== b . 889.09 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 images/sec > Higher Is Better a . 104.53 |=================================================================== b . 104.61 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: VGG-16 images/sec > Higher Is Better a . 39.78 |==================================================================== b . 39.79 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: GoogLeNet images/sec > Higher Is Better a . 320.31 |=================================================================== b . 320.23 |=================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: VGG-16 images/sec > Higher Is Better a . 44.69 |==================================================================== b . 44.70 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 512 - Model: GoogLeNet images/sec > Higher Is Better a . 326.63 |=================================================================== b . 326.60 |=================================================================== Blender 4.1 Blend File: Junkshop - Compute: CPU-Only Seconds < Lower Is Better a . 34.32 |==================================================================== b . 34.32 |====================================================================