Dell Inc. PowerEdge R7625
Geekbench AI Score
32267
Single Precision Score
45676
Half Precision Score
24547
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | kngtrider |
| Upload Date | August 15 2024 07:42 PM |
| Views | 28 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA L40S |
| System Information | |
|---|---|
| Operating System | Microsoft Windows Server 2022 Standard (64-bit) |
| Model | Dell Inc. PowerEdge R7625 |
| Motherboard | Dell Inc. 0H1TJT |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | AMD EPYC 9184X |
| Topology | 2 Processors, 32 Cores, 64 Threads |
| Identifier | AuthenticAMD Family 25 Model 17 Stepping 2 |
| Base Frequency | 3.55 GHz |
| Cluster 1 | 32 Cores |
| Memory Information | |
|---|---|
| Size | 512.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11395
2.12 KIPS |
|
|
Image Classification (HP)
|
99% |
14874
2.77 KIPS |
|
|
Image Classification (Q)
|
100% |
9704
1.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20591
333.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
25266
409.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
19282
313.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
272234
317.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
604101
704.9 IPS |
|
|
Pose Estimation (Q)
|
97% |
238704
279.5 IPS |
|
|
Object Detection (SP)
|
100% |
16395
1.30 KIPS |
|
|
Object Detection (HP)
|
100% |
21729
1.72 KIPS |
|
|
Object Detection (Q)
|
89% |
13995
1.12 KIPS |
|
|
Face Detection (SP)
|
100% |
45056
535.4 IPS |
|
|
Face Detection (HP)
|
100% |
57796
686.7 IPS |
|
|
Face Detection (Q)
|
97% |
37982
452.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
79189
610.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
135267
1.04 KIPS |
|
|
Depth Estimation (Q)
|
78% |
59745
477.2 IPS |
|
|
Style Transfer (SP)
|
100% |
483413
621.4 IPS |
|
|
Style Transfer (HP)
|
100% |
960061
1.23 KIPS |
|
|
Style Transfer (Q)
|
98% |
418396
539.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
50667
1.87 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
67938
2.51 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37903
1.40 KIPS |
|
|
Text Classification (SP)
|
100% |
2919
3.90 KIPS |
|
|
Text Classification (HP)
|
99% |
3522
4.70 KIPS |
|
|
Text Classification (Q)
|
97% |
1833
2.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
4580
78.9 IPS |
|
|
Machine Translation (HP)
|
100% |
4462
76.9 IPS |
|
|
Machine Translation (Q)
|
60% |
1927
43.0 IPS |
