Summary
AI & Machine Learning
Energy
Financial Services
Life Sciences
Media & Entertainment
Product Design
Productivity & Development
Subsystem Scores
Workload Scores
Configuration
SPECworkstation® 4.0.0 Summary
Not An Official Submission Candidate
19 of 21 workloads produced scores
System Configuration
| Manufacturer | ASUSTeK COMPUTER INC. |
| Model | RS720A-E13-RS8G |
| CPU | 2x AMD EPYC 9115 16-Core Processor |
| Memory | 64.00 GB @ 4800 MHz |
| GPU | ASPEED Graphics Family(WDDM) |
| Display | Unknown |
| Storage | Drive 1: BROADCOM MR9560-16i SCSI Disk Device 893.75 GB - SCSI Drive 2: INTEL SSDPEKKA256G8 238.47 GB - SCSI Drive 3: INTEL SSDPEKKA256G8 238.47 GB - SCSI Drive 4: SanDisk Ultra Fit USB Device 28.63 GB - USB |
| OS | Microsoft Windows Server 2025 Standard (26100) |
Submission Details
| Result Date | Mon Apr 06 2026 01:13:26 GMT+0300 (GMT+03:00) |
| Submitter Company | |
| Submitter Name | |
| Submitter Comments |
Industry Vertical Scores
Financial Services |
3.21 |
Hardware Subsystem Scores
| CPU | 2.26 |
| Workload | SPEC Ratio |
|---|---|
| 7-Zip | 0.95 |
| Autodesk Inventor | 0.94 |
| Blender | 3.01 |
| Convolution | 3.79 |
| Data Science | 1.62 |
| Hidden Line Removal | 1.40 |
| LAMMPS | 2.89 |
| LLVM Clang | 2.76 |
| LuxCoreRender | 2.99 |
| MFEM | 2.30 |
| NAMD | 2.69 |
| Octave | 1.00 |
| OpenFOAM | 14.60 |
| Options Pricing | 3.21 |
| Poisson | 2.70 |
| Python 3 | 1.28 |
| Rodinia CFD | 1.91 |
| Rodinia Life Sciences | 2.79 |
| SRMP | 2.40 |
Industry Vertical Scores
| AI & Machine Learning | ||||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Data Science |
|
|||
| Pandas | 131.99 |
143.85
|
sec |
0.92
|
| Scikit-learn | 449.17 |
155.61
|
sec |
2.89
|
| XGBoost | 91.50 |
56.88
|
sec |
1.61
|
| ONNX Inference |
|
|||
| CPU ResNet50-FP32-batch8 Latency | 63.72 |
24.24
|
ms |
2.63
|
| CPU ResNet50-FP32-batch8 Throughput | 18.33 |
48.72
|
inferences/sec |
2.66
|
| CPU ResNet50-INT8-batch8 Latency | 22.37 |
11.32
|
ms |
1.98
|
| CPU ResNet50-INT8-batch8 Throughput | 46.62 |
150.24
|
inferences/sec |
3.22
|
| CPU SuperResolution-FP32-batch8 Latency | 58.42 |
27.83
|
ms |
2.10
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.87 |
67.48
|
inferences/sec |
3.23
|
| CPU SuperResolution-INT8-batch8 Latency | 21.34 |
26.09
|
ms |
0.82
|
| CPU SuperResolution-INT8-batch8 Throughput | 55.92 |
107.84
|
inferences/sec |
1.93
|
Industry Vertical Scores
| Energy | ||||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Convolution |
|
|||
| 20K/100 | 0.09 |
0.34
|
iterations/sec |
3.79
|
| Poisson |
|
|||
| Jacobi Rectangular Grid | 16.05 |
59.73
|
iterations/sec |
3.72
|
| Jacobi Square Grid | 6.19 |
12.14
|
iterations/sec |
1.96
|
| SRMP |
|
|||
| 2D | 19.45 |
8.10
|
sec |
2.40
|
Industry Vertical Scores
| Financial Services | 3.21 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Options Pricing |
|
|||
| Monte Carlo | 35137.48 |
127501.00
|
options/sec |
3.63
|
| Black-Scholes | 3389.63 |
12242.00
|
Moptions/sec |
3.61
|
| Binomial | 79377.62 |
200167.90
|
options/sec |
2.52
|
Industry Vertical Scores
| Life Sciences | ||||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| LAMMPS |
|
|||
| LJ | 705.82 |
2168.80
|
tau/day |
3.07
|
| CHAIN | 1190.35 |
3511.48
|
tau/day |
2.95
|
| EAM | 0.63 |
1.99
|
ns/day |
3.16
|
| CHUTE | 38.25 |
91.01
|
tau/day |
2.38
|
| RHODO | 0.26 |
0.76
|
ns/day |
2.94
|
| NAMD |
|
|||
| apoa1 | 45.38 |
17.44
|
ms/step |
2.60
|
| f1atpase | 130.50 |
49.96
|
ms/step |
2.61
|
| stmv | 448.57 |
156.06
|
ms/step |
2.87
|
| Rodinia Life Sciences |
|
|||
| Heart Wall | 0.69 |
2.44
|
fps |
3.53
|
| HotSpot | 8.55 |
3.34
|
sec |
2.56
|
| LavaMD | 0.07 |
0.24
|
iterations/sec |
3.49
|
| SRAD | 47.04 |
90.13
|
iterations/sec |
1.92
|
Industry Vertical Scores
| Media & Entertainment | ||||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Blender |
|
|||
| Classroom | 281.72 |
30.12
|
sec |
9.35
|
| BMW27 | 43.82 |
15.06
|
sec |
2.91
|
| BMW1M | 17.74 |
6.09
|
sec |
2.91
|
| Island | 29.68 |
28.80
|
sec |
1.03
|
| HandBrake |
|
|||
| SVT-AV1 8K to 4K | 195.16 |
101.76
|
sec |
1.92
|
| x265 4K to 1080p | 38.36 |
23.41
|
sec |
1.64
|
| x265 4K to 4K | 107.73 |
56.77
|
sec |
1.90
|
| x264 1080p to 1080p | 49.98 |
8.33
|
sec |
6.00
|
| LuxCoreRender |
|
|||
| DLSC | 2.46 |
8.14
|
Msamples/sec |
3.31
|
| Food | 1.84 |
5.94
|
Msamples/sec |
3.23
|
| Danish Mood | 2.29 |
5.26
|
Msamples/sec |
2.30
|
| Procedural Leaves | 1.10 |
3.57
|
Msamples/sec |
3.25
|
Industry Vertical Scores
| Product Design | ||||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Autodesk Inventor |
|
|||
| Open Document | 4253.73 |
4463.00
|
ms |
0.95
|
| Create/Update Files | 4973.68 |
5866.00
|
ms |
0.85
|
| Rebuild | 10590.28 |
11431.00
|
ms |
0.93
|
| Render Style/Material | 628.78 |
615.00
|
ms |
1.02
|
| Hidden Line Removal |
|
|||
| Palatov | 24.29 |
34.00
|
fps |
1.40
|
| MFEM |
|
|||
| Dynamic AMR | 227.39 |
98.66
|
sec |
2.30
|
| OpenFOAM |
|
|||
| XiFoam Solver | 803.27 |
55.19
|
sec |
14.60
|
| Rodinia CFD |
|
|||
| Pre-Euler | 138.14 |
263.37
|
iterations/sec |
1.91
|
Industry Vertical Scores
| Productivity & Development | ||||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| 7-Zip |
|
|||
| Decompression | 16.04 |
22.01
|
sec |
0.73
|
| Compression | 254.57 |
237.38
|
sec |
1.07
|
| LLVM Clang |
|
|||
| PyTorch | 562.76 |
204.04
|
sec |
2.76
|
| Octave |
|
|||
| obench | 1.20 |
1.17
|
sec/operation |
1.03
|
| benchmark2 | 0.11 |
0.11
|
sec/operation |
0.97
|
| Python 3 |
|
|||
| NumPy Create Matrix | 0.36 |
0.53
|
sec |
0.68
|
| NumPy Add Matrix | 4.44 |
4.88
|
sec |
0.91
|
| NumPy Multiply Matrix | 8.06 |
6.98
|
sec |
1.15
|
| NumPy Invert Matrix | 15.53 |
13.89
|
sec |
1.12
|
| NumPy Sin Matrix | 2.67 |
3.00
|
sec |
0.89
|
| Multi-Matrix | 65.50 |
37.54
|
sec |
1.74
|
Hardware Subsystem Scores
Hardware Subsystem
SPEC Ratio
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|
2.26
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| 7-Zip |
|
|||
| Decompression | 16.04 |
22.01
|
sec |
0.73
|
| Compression | 254.57 |
237.38
|
sec |
1.07
|
| Autodesk Inventor |
|
|||
| Open Document | 4253.73 |
4463.00
|
ms |
0.95
|
| Create/Update Files | 4973.68 |
5866.00
|
ms |
0.85
|
| Rebuild | 10590.28 |
11431.00
|
ms |
0.93
|
| Render Style/Material | 628.78 |
615.00
|
ms |
1.02
|
| Blender |
|
|||
| Classroom | 281.72 |
30.12
|
sec |
9.35
|
| BMW27 | 43.82 |
15.06
|
sec |
2.91
|
| BMW1M | 17.74 |
6.09
|
sec |
2.91
|
| Island | 29.68 |
28.80
|
sec |
1.03
|
| Convolution |
|
|||
| 20K/100 | 0.09 |
0.34
|
iterations/sec |
3.79
|
| Data Science |
|
|||
| Pandas | 131.99 |
143.85
|
sec |
0.92
|
| Scikit-learn | 449.17 |
155.61
|
sec |
2.89
|
| XGBoost | 91.50 |
56.88
|
sec |
1.61
|
| HandBrake |
|
|||
| SVT-AV1 8K to 4K | 195.16 |
101.76
|
sec |
1.92
|
| x265 4K to 1080p | 38.36 |
23.41
|
sec |
1.64
|
| x265 4K to 4K | 107.73 |
56.77
|
sec |
1.90
|
| x264 1080p to 1080p | 49.98 |
8.33
|
sec |
6.00
|
| Hidden Line Removal |
|
|||
| Palatov | 24.29 |
34.00
|
fps |
1.40
|
| LAMMPS |
|
|||
| LJ | 705.82 |
2168.80
|
tau/day |
3.07
|
| CHAIN | 1190.35 |
3511.48
|
tau/day |
2.95
|
| EAM | 0.63 |
1.99
|
ns/day |
3.16
|
| CHUTE | 38.25 |
91.01
|
tau/day |
2.38
|
| RHODO | 0.26 |
0.76
|
ns/day |
2.94
|
| LLVM Clang |
|
|||
| PyTorch | 562.76 |
204.04
|
sec |
2.76
|
| LuxCoreRender |
|
|||
| DLSC | 2.46 |
8.14
|
Msamples/sec |
3.31
|
| Food | 1.84 |
5.94
|
Msamples/sec |
3.23
|
| Danish Mood | 2.29 |
5.26
|
Msamples/sec |
2.30
|
| Procedural Leaves | 1.10 |
3.57
|
Msamples/sec |
3.25
|
| MFEM |
|
|||
| Dynamic AMR | 227.39 |
98.66
|
sec |
2.30
|
| NAMD |
|
|||
| apoa1 | 45.38 |
17.44
|
ms/step |
2.60
|
| f1atpase | 130.50 |
49.96
|
ms/step |
2.61
|
| stmv | 448.57 |
156.06
|
ms/step |
2.87
|
| Octave |
|
|||
| obench | 1.20 |
1.17
|
sec/operation |
1.03
|
| benchmark2 | 0.11 |
0.11
|
sec/operation |
0.97
|
| ONNX Inference |
|
|||
| CPU ResNet50-FP32-batch8 Latency | 63.72 |
24.24
|
ms |
2.63
|
| CPU ResNet50-FP32-batch8 Throughput | 18.33 |
48.72
|
inferences/sec |
2.66
|
| CPU ResNet50-INT8-batch8 Latency | 22.37 |
11.32
|
ms |
1.98
|
| CPU ResNet50-INT8-batch8 Throughput | 46.62 |
150.24
|
inferences/sec |
3.22
|
| CPU SuperResolution-FP32-batch8 Latency | 58.42 |
27.83
|
ms |
2.10
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.87 |
67.48
|
inferences/sec |
3.23
|
| CPU SuperResolution-INT8-batch8 Latency | 21.34 |
26.09
|
ms |
0.82
|
| CPU SuperResolution-INT8-batch8 Throughput | 55.92 |
107.84
|
inferences/sec |
1.93
|
| OpenFOAM |
|
|||
| XiFoam Solver | 803.27 |
55.19
|
sec |
14.60
|
| Options Pricing |
|
|||
| Monte Carlo | 35137.48 |
127501.00
|
options/sec |
3.63
|
| Black-Scholes | 3389.63 |
12242.00
|
Moptions/sec |
3.61
|
| Binomial | 79377.62 |
200167.90
|
options/sec |
2.52
|
| Poisson |
|
|||
| Jacobi Rectangular Grid | 16.05 |
59.73
|
iterations/sec |
3.72
|
| Jacobi Square Grid | 6.19 |
12.14
|
iterations/sec |
1.96
|
| Python 3 |
|
|||
| NumPy Create Matrix | 0.36 |
0.53
|
sec |
0.68
|
| NumPy Add Matrix | 4.44 |
4.88
|
sec |
0.91
|
| NumPy Multiply Matrix | 8.06 |
6.98
|
sec |
1.15
|
| NumPy Invert Matrix | 15.53 |
13.89
|
sec |
1.12
|
| NumPy Sin Matrix | 2.67 |
3.00
|
sec |
0.89
|
| Multi-Matrix | 65.50 |
37.54
|
sec |
1.74
|
| Rodinia CFD |
|
|||
| Pre-Euler | 138.14 |
263.37
|
iterations/sec |
1.91
|
| Rodinia Life Sciences |
|
|||
| Heart Wall | 0.69 |
2.44
|
fps |
3.53
|
| HotSpot | 8.55 |
3.34
|
sec |
2.56
|
| LavaMD | 0.07 |
0.24
|
iterations/sec |
3.49
|
| SRAD | 47.04 |
90.13
|
iterations/sec |
1.92
|
| SRMP |
|
|||
| 2D | 19.45 |
8.10
|
sec |
2.40
|
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|
Workload Scores
| Workload | Time Stamp | Execution Time | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|---|---|
| 7-Zip | Apr 6, 2026, 1:13:26 AM GMT+3 |
0.95
|
||||
| Decompression | 22.01 sec | 16.04 |
22.01
|
sec |
0.73
|
|
| Compression | 237.38 sec | 254.57 |
237.38
|
sec |
1.07
|
|
| Autodesk Inventor | Apr 6, 2026, 1:17:50 AM GMT+3 |
0.94
|
||||
| Open Document | 4.67 sec | 4253.73 |
4463.00
|
ms |
0.95
|
|
| Create/Update Files | 7.73 sec | 4973.68 |
5866.00
|
ms |
0.85
|
|
| Rebuild | 11.64 sec | 10590.28 |
11431.00
|
ms |
0.93
|
|
| Render Style/Material | 0.83 sec | 628.78 |
615.00
|
ms |
1.02
|
|
| Blender | Apr 6, 2026, 1:18:56 AM GMT+3 |
3.01
|
||||
| Classroom | 30.12 sec | 281.72 |
30.12
|
sec |
9.35
|
|
| BMW27 | 15.06 sec | 43.82 |
15.06
|
sec |
2.91
|
|
| BMW1M | 6.09 sec | 17.74 |
6.09
|
sec |
2.91
|
|
| Island | 28.80 sec | 29.68 |
28.80
|
sec |
1.03
|
|
| Convolution | Apr 6, 2026, 1:20:21 AM GMT+3 |
3.79
|
||||
| 20K/100 | 34.24 sec | 0.09 |
0.34
|
iterations/sec |
3.79
|
|
| Data Science | Apr 6, 2026, 1:20:55 AM GMT+3 |
1.62
|
||||
| Pandas | 156.59 sec | 131.99 |
143.85
|
sec |
0.92
|
|
| Scikit-learn | 160.43 sec | 449.17 |
155.61
|
sec |
2.89
|
|
| XGBoost | 79.55 sec | 91.50 |
56.88
|
sec |
1.61
|
|
| HandBrake | Apr 6, 2026, 1:27:49 AM GMT+3 |
|
||||
| SVT-AV1 8K to 4K | 101.76 sec | 195.16 |
101.76
|
sec |
1.92
|
|
| x265 4K to 1080p | 24.69 sec | 38.36 |
23.41
|
sec |
1.64
|
|
| x265 4K to 4K | 58.28 sec | 107.73 |
56.77
|
sec |
1.90
|
|
| x264 1080p to 1080p | 8.33 sec | 49.98 |
8.33
|
sec |
6.00
|
|
| Hidden Line Removal | Apr 6, 2026, 1:31:09 AM GMT+3 |
1.40
|
||||
| Palatov | 18.82 sec | 24.29 |
34.00
|
fps |
1.40
|
|
| Palatov | 18.60 sec | 24.29 |
29.91
|
fps |
1.23
|
|
| LAMMPS | Apr 6, 2026, 1:31:48 AM GMT+3 |
2.89
|
||||
| LJ | 7.22 sec | 705.82 |
2168.80
|
tau/day |
3.07
|
|
| CHAIN | 7.75 sec | 1190.35 |
3511.48
|
tau/day |
2.95
|
|
| EAM | 7.29 sec | 0.63 |
1.99
|
ns/day |
3.16
|
|
| CHUTE | 4.99 sec | 38.25 |
91.01
|
tau/day |
2.38
|
|
| RHODO | 4.58 sec | 0.26 |
0.76
|
ns/day |
2.94
|
|
| LLVM Clang | Apr 6, 2026, 1:32:20 AM GMT+3 |
2.76
|
||||
| PyTorch | 222.59 sec | 562.76 |
204.04
|
sec |
2.76
|
|
| LuxCoreRender | Apr 6, 2026, 1:37:33 AM GMT+3 |
2.99
|
||||
| DLSC | 7.77 sec | 2.46 |
8.14
|
Msamples/sec |
3.31
|
|
| Food | 12.55 sec | 1.84 |
5.94
|
Msamples/sec |
3.23
|
|
| Danish Mood | 29.30 sec | 2.29 |
5.26
|
Msamples/sec |
2.30
|
|
| Procedural Leaves | 16.10 sec | 1.10 |
3.57
|
Msamples/sec |
3.25
|
|
| MFEM | Apr 6, 2026, 1:38:39 AM GMT+3 |
2.30
|
||||
| Dynamic AMR | 98.66 sec | 227.39 |
98.66
|
sec |
2.30
|
|
| NAMD | Apr 6, 2026, 1:40:18 AM GMT+3 |
2.69
|
||||
| apoa1 | 10.26 sec | 45.38 |
17.44
|
ms/step |
2.60
|
|
| f1atpase | 18.12 sec | 130.50 |
49.96
|
ms/step |
2.61
|
|
| stmv | 34.85 sec | 448.57 |
156.06
|
ms/step |
2.87
|
|
| Octave | Apr 6, 2026, 1:41:22 AM GMT+3 |
1.00
|
||||
| obench | 37.00 sec | 1.20 |
1.17
|
sec/operation |
1.03
|
|
| benchmark2 | 11.89 sec | 0.11 |
0.11
|
sec/operation |
0.97
|
|
| ONNX Inference | Apr 6, 2026, 1:42:23 AM GMT+3 |
|
||||
| CPU ResNet50-FP32-batch8 Latency | 20.32 sec | 63.72 |
24.24
|
ms |
2.63
|
|
| CPU ResNet50-FP32-batch8 Throughput | 21.41 sec | 18.33 |
48.72
|
inferences/sec |
2.66
|
|
| CPU ResNet50-FP32-batch8 Throughput | 21.86 sec | 18.33 |
40.78
|
inferences/sec |
2.22
|
|
| CPU ResNet50-INT8-batch8 Latency | 20.16 sec | 22.37 |
11.32
|
ms |
1.98
|
|
| CPU ResNet50-INT8-batch8 Throughput | 20.52 sec | 46.62 |
150.24
|
inferences/sec |
3.22
|
|
| CPU ResNet50-INT8-batch8 Throughput | 20.70 sec | 46.62 |
126.46
|
inferences/sec |
2.71
|
|
| CPU SuperResolution-FP32-batch8 Latency | 20.12 sec | 58.42 |
27.83
|
ms |
2.10
|
|
| CPU SuperResolution-FP32-batch8 Throughput | 21.04 sec | 20.87 |
67.48
|
inferences/sec |
3.23
|
|
| CPU SuperResolution-FP32-batch8 Throughput | 21.92 sec | 20.87 |
39.18
|
inferences/sec |
1.88
|
|
| CPU SuperResolution-INT8-batch8 Latency | 20.13 sec | 21.34 |
26.09
|
ms |
0.82
|
|
| CPU SuperResolution-INT8-batch8 Throughput | 20.75 sec | 55.92 |
107.84
|
inferences/sec |
1.93
|
|
| CPU SuperResolution-INT8-batch8 Throughput | 20.91 sec | 55.92 |
79.02
|
inferences/sec |
1.41
|
|
| OpenFOAM | Apr 6, 2026, 1:46:34 AM GMT+3 |
14.60
|
||||
| XiFoam Solver | 85.27 sec | 803.27 |
67.93
|
sec |
11.80
|
|
| XiFoam Solver | 67.51 sec | 803.27 |
55.19
|
sec |
14.60
|
|
| Options Pricing | Apr 6, 2026, 1:49:12 AM GMT+3 |
3.21
|
||||
| Monte Carlo | 8.35 sec | 35137.48 |
127501.00
|
options/sec |
3.63
|
|
| Black-Scholes | 6.92 sec | 3389.63 |
12242.00
|
Moptions/sec |
3.61
|
|
| Binomial | 5.31 sec | 79377.62 |
200167.90
|
options/sec |
2.52
|
|
| Poisson | Apr 6, 2026, 1:49:32 AM GMT+3 |
2.70
|
||||
| Jacobi Rectangular Grid | 10.09 sec | 16.05 |
59.73
|
iterations/sec |
3.72
|
|
| Jacobi Rectangular Grid | 10.07 sec | 16.05 |
24.60
|
iterations/sec |
1.53
|
|
| Jacobi Square Grid | 10.08 sec | 6.19 |
12.14
|
iterations/sec |
1.96
|
|
| Jacobi Square Grid | 10.09 sec | 6.19 |
8.24
|
iterations/sec |
1.33
|
|
| Python 3 | Apr 6, 2026, 1:50:13 AM GMT+3 |
1.28
|
||||
| NumPy Create Matrix | 2.69 sec | 0.36 |
0.53
|
sec |
0.68
|
|
| NumPy Add Matrix | 5.71 sec | 4.44 |
4.88
|
sec |
0.91
|
|
| NumPy Multiply Matrix | 7.83 sec | 8.06 |
6.98
|
sec |
1.15
|
|
| NumPy Invert Matrix | 14.77 sec | 15.53 |
13.89
|
sec |
1.12
|
|
| NumPy Sin Matrix | 3.83 sec | 2.67 |
3.00
|
sec |
0.89
|
|
| Multi-Matrix | 38.41 sec | 65.50 |
37.54
|
sec |
1.74
|
|
| Rodinia CFD | Apr 6, 2026, 1:51:37 AM GMT+3 |
1.91
|
||||
| Pre-Euler | 33.22 sec | 138.14 |
263.37
|
iterations/sec |
1.91
|
|
| Rodinia Life Sciences | Apr 6, 2026, 1:52:11 AM GMT+3 |
2.79
|
||||
| Heart Wall | 10.57 sec | 0.69 |
2.44
|
fps |
3.53
|
|
| HotSpot | 4.54 sec | 8.55 |
3.34
|
sec |
2.56
|
|
| LavaMD | 12.71 sec | 0.07 |
0.24
|
iterations/sec |
3.49
|
|
| SRAD | 10.27 sec | 47.04 |
90.13
|
iterations/sec |
1.92
|
|
| SRMP | Apr 6, 2026, 1:52:50 AM GMT+3 |
2.40
|
||||
| 2D | 8.47 sec | 19.45 |
8.10
|
sec |
2.40
|
System Configuration Details
MOTHERBOARD
Name: K15PP-D24 SeriesModel: RS720A-E13-RS8G
Version: 60SB0D10-SB0B02
Manufacturer: ASUSTeK COMPUTER INC.
Serial Number: 250657861200360
BIOS: American Megatrends Inc. 1002
BIOS Version: AMD - 3042021 (2025-10-14)
PROCESSOR
CPU #1: AMD EPYC 9115 16-Core Processor (2600MHz / 16C / 32T)CPU #2: AMD EPYC 9115 16-Core Processor (2600MHz / 16C / 32T)
MEMORY
P0 CHANNEL A (CPU1_DIMM_A1): Samsung M321R2GA3BB6-CQKET (16.00 GB / 4800 MHz / DDR5)P0 CHANNEL G (CPU1_DIMM_G1): Samsung M321R2GA3BB6-CQKET (16.00 GB / 4800 MHz / DDR5)
P1 CHANNEL A (CPU2_DIMM_A1): Samsung M321R2GA3BB6-CQKET (16.00 GB / 4800 MHz / DDR5)
P1 CHANNEL G (CPU2_DIMM_G1): Samsung M321R2GA3BB6-CQKET (16.00 GB / 4800 MHz / DDR5)
Total Memory: 64.00 GB
STORAGE
Disk #1: BROADCOM MR9560-16i SCSI Disk Device (893.75 GB - SCSI)Disk #2: INTEL SSDPEKKA256G8 (238.47 GB - SCSI)
Partition 1: GPT: System (0.20 GB)
Partition 2: GPT: Basic Data (237.47 GB)
Partition 3: GPT: Unknown (0.79 GB)
Disk #3: INTEL SSDPEKKA256G8 (238.47 GB - SCSI)
Disk #4: SanDisk Ultra Fit USB Device (28.63 GB - USB)
Partition 1: GPT: Basic Data (28.64 GB)
Partition 2: GPT: Basic Data (0.00 GB)
Available Volumes
C: (): NTFS (192.26 GB of 237.47 GB Available)
NETWORK
Adapter #1: Intel(R) Ethernet Converged Network Adapter X540-T1Type: Ethernet 802.3 | MAC: A0:36:9F:73:B5:A4 | Speed: 1000.00 Mbit
GRAPHICS
Adapter #1: ASPEED Graphics Family(WDDM)Video Memory: 0.06 GB
Current Resolution: 1920x1080 @ 60 Hz (32-bit Color)
Driver Version: 9.0.10.116 (2026-02-10)
DISPLAY
No Physical Displays DetectedWindows Screens
Screen 1: 1920x1080 @ 32 bpp
OPERATING SYSTEM
Name: Microsoft Windows Server 2025 Standard 64-bitVersion: 10.0.26100.32522 (Release 2009)
Installation Date: 2026-04-01
Free Memory: 59.25 GB (Physical) | 68.20 GB (Virtual) | 9.50 GB (Paging)
Screensaver: Disabled
Visual Effects Setting: Let Windows Choose
Virtualization Based Security (VBS): Not Running
Active Power Plan: High performance (8c5e7fda-e8bf-4a96-9a85-a6e23a8c635c)