OpenStack Foundation OpenStack Nova
Geekbench ML Score
9527
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | May 07 2024 07:31 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows Server 2019 Datacenter (64-bit) |
| Model | OpenStack Foundation OpenStack Nova |
| Motherboard | |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD EPYC-Rome Processor |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 23 Model 49 Stepping 0 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 16 Cores |
| L1 Instruction Cache | 32.0 KB x 16 |
| L1 Data Cache | 32.0 KB x 16 |
| L2 Cache | 512 KB x 16 |
| L3 Cache | 4.00 MB x 4 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Type | RAM |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA RTX A4000 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4795
897.2 IPS |
|
|
Image Classification (F16)
|
100% |
4455
833.6 IPS |
|
|
Image Classification (I8)
|
100% |
3561
666.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
7404
123.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
4828
80.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
5757
96.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
83951
101.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
79914
96.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
67867
82.2 IPS |
|
|
Object Detection (F32)
|
100% |
2860
213.5 IPS |
|
|
Object Detection (F16)
|
100% |
2966
221.5 IPS |
|
|
Object Detection (I8)
|
63% |
2768
206.6 IPS |
|
|
Face Detection (F32)
|
100% |
13281
157.9 IPS |
|
|
Face Detection (F16)
|
100% |
12267
145.9 IPS |
|
|
Face Detection (I8)
|
89% |
10204
121.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
32227
249.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
36254
281.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
24758
192.0 IPS |
|
|
Style Transfer (F32)
|
100% |
130141
171.2 IPS |
|
|
Style Transfer (F16)
|
100% |
128815
169.4 IPS |
|
|
Style Transfer (I8)
|
98% |
102981
135.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
20905
746.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
20313
725.5 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
13586
485.2 IPS |
|
|
Text Classification (F32)
|
100% |
1445
2.08 KIPS |
|
|
Text Classification (F16)
|
100% |
1386
1.99 KIPS |
|
|
Text Classification (I8)
|
98% |
881
1.27 KIPS |
|
|
Machine Translation (F32)
|
100% |
1381
25.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1407
25.9 IPS |
|
|
Machine Translation (I8)
|
70% |
853
15.7 IPS |
