Congatec GmbH conga-HPC/sILL
Geekbench AI Score
162
Single Precision Score
153
Half Precision Score
156
Quantized Score
Geekbench AI 1.1.0 for Linux AVX2
Result Information
| Upload Date | November 20 2024 02:22 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Xeon D-2899NT |
| System Information | |
|---|---|
| Operating System | Ubuntu 22.04.5 LTS |
| Model | Congatec GmbH conga-HPC/sILL |
| Motherboard | Congatec GmbH conga-HPC/EVAL-Server |
| CPU Information | |
|---|---|
| Name | Intel Xeon D-2899NT |
| Topology | 1 Processor, 22 Cores, 44 Threads |
| Identifier | GenuineIntel Family 6 Model 108 Stepping 1 |
| Base Frequency | 3.10 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 62.39 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1227
228.2 IPS |
|
|
Image Classification (HP)
|
100% |
764
142.1 IPS |
|
|
Image Classification (Q)
|
99% |
641
119.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
558
9.05 IPS |
|
|
Image Segmentation (HP)
|
100% |
682
11.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
487
7.91 IPS |
|
|
Pose Estimation (SP)
|
100% |
1158
1.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
761
0.89 IPS |
|
|
Pose Estimation (Q)
|
96% |
841
0.99 IPS |
|
|
Object Detection (SP)
|
100% |
56
4.45 IPS |
|
|
Object Detection (HP)
|
100% |
52
4.16 IPS |
|
|
Object Detection (Q)
|
85% |
51
4.09 IPS |
|
|
Face Detection (SP)
|
100% |
252
3.00 IPS |
|
|
Face Detection (HP)
|
100% |
200
2.38 IPS |
|
|
Face Detection (Q)
|
97% |
204
2.43 IPS |
|
|
Depth Estimation (SP)
|
100% |
167
1.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
163
1.26 IPS |
|
|
Depth Estimation (Q)
|
63% |
138
1.30 IPS |
|
|
Style Transfer (SP)
|
100% |
1123
1.44 IPS |
|
|
Style Transfer (HP)
|
100% |
1026
1.32 IPS |
|
|
Style Transfer (Q)
|
98% |
1796
2.32 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
87
3.22 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
91
3.37 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
90
3.34 IPS |
|
|
Text Classification (SP)
|
100% |
5
6.90 IPS |
|
|
Text Classification (HP)
|
100% |
9
12.5 IPS |
|
|
Text Classification (Q)
|
92% |
6
8.11 IPS |
|
|
Machine Translation (SP)
|
100% |
14
0.25 IPS |
|
|
Machine Translation (HP)
|
100% |
13
0.23 IPS |
|
|
Machine Translation (Q)
|
58% |
24
0.56 IPS |
