Congatec GmbH conga-HPC/sILL
Geekbench AI Score
2842
Single Precision Score
1079
Half Precision Score
2997
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 21 2024 09:32 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Xeon D-2899NT |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Congatec GmbH conga-HPC/sILL |
| Motherboard | Congatec GmbH conga-HPC/EVAL-Server |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Xeon D-2899NT |
| Topology | 1 Processor, 22 Cores, 44 Threads |
| Identifier | GenuineIntel Family 6 Model 108 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 22 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
825
153.4 IPS |
|
|
Image Classification (HP)
|
100% |
259
48.1 IPS |
|
|
Image Classification (Q)
|
99% |
2147
400.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1206
19.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
615
9.97 IPS |
|
|
Image Segmentation (Q)
|
98% |
1858
30.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
9456
11.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
5584
6.52 IPS |
|
|
Pose Estimation (Q)
|
95% |
28752
33.7 IPS |
|
|
Object Detection (SP)
|
100% |
1829
145.1 IPS |
|
|
Object Detection (HP)
|
100% |
414
32.9 IPS |
|
|
Object Detection (Q)
|
88% |
1331
106.7 IPS |
|
|
Face Detection (SP)
|
100% |
3218
38.2 IPS |
|
|
Face Detection (HP)
|
100% |
1063
12.6 IPS |
|
|
Face Detection (Q)
|
97% |
2964
35.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7482
57.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
1451
11.2 IPS |
|
|
Depth Estimation (Q)
|
77% |
6050
48.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20326
26.1 IPS |
|
|
Style Transfer (HP)
|
100% |
13298
17.1 IPS |
|
|
Style Transfer (Q)
|
98% |
17353
22.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2615
96.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2004
74.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2947
109.1 IPS |
|
|
Text Classification (SP)
|
100% |
1103
1.47 KIPS |
|
|
Text Classification (HP)
|
100% |
410
547.1 IPS |
|
|
Text Classification (Q)
|
97% |
310
415.5 IPS |
|
|
Machine Translation (SP)
|
100% |
1420
24.5 IPS |
|
|
Machine Translation (HP)
|
100% |
347
5.98 IPS |
|
|
Machine Translation (Q)
|
60% |
1348
30.1 IPS |
