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
Official Submission Candidate
23 of 23 workloads produced scores
System Configuration
| Manufacturer | LENOVO |
| Model | Lenovo ThinkPad P1 Gen 6 |
| CPU | 13th Gen Intel(R) Core(TM) i9-13900H |
| Memory | 64.00 GB @ 5600 MHz |
| GPU | 1x Intel(R) Iris(R) Xe Graphics 1x NVIDIA RTX 5000 Ada Generation Laptop GPU |
| Display | Internal Display 15.9" (3840x2400) |
| Storage | KXG8AZN84T09 LA KIOXIA 3815.44 GB - SCSI |
| OS | Microsoft Windows 11 Pro (26100) |
Submission Details
| Result Date | Wed Nov 20 2024 21:41:49 GMT-0500 (Eastern Standard Time) |
| Submitter Company | |
| Submitter Name | |
| Submitter Comments |
Industry Vertical Scores
AI & Machine Learning |
1.67 |
Energy |
1.63 |
Financial Services |
0.83 |
Life Sciences |
1.79 |
Media & Entertainment |
1.86 |
Product Design |
1.65 |
Productivity & Development |
1.21 |
Hardware Subsystem Scores
| CPU | 1.17 |
| Accelerator | 4.60 |
| Graphics | 7.91 |
| Storage | 1.19 |
| Workload | SPEC Ratio |
|---|---|
| 7-Zip | 2.95 |
| Autodesk Inventor | 0.63 |
| Blender | 1.25 |
| Convolution | 0.95 |
| Data Science | 1.37 |
| HandBrake | 1.46 |
| Hidden Line Removal | 1.10 |
| LAMMPS | 1.17 |
| LLVM Clang | 1.06 |
| LuxCoreRender | 1.05 |
| MFEM | 0.97 |
| NAMD | 1.03 |
| Octave | 1.14 |
| ONNX Inference | 2.03 |
| OpenFOAM | 5.22 |
| Options Pricing | 0.83 |
| Poisson | 1.27 |
| Python 3 | 1.00 |
| Rodinia CFD | 1.44 |
| Rodinia Life Sciences | 1.04 |
| SRMP | 0.84 |
| Viewport Graphics | 7.91 |
| WPCstorage | 1.19 |
Industry Vertical Scores
| AI & Machine Learning | 1.67 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Data Science |
|
|||
| Pandas | 131.99 |
110.04
|
sec |
1.20
|
| Scikit-learn | 449.17 |
331.14
|
sec |
1.36
|
| XGBoost | 91.50 |
57.65
|
sec |
1.59
|
| ONNX Inference |
|
|||
| CPU ResNet50-FP32-batch8 Latency | 63.72 |
78.94
|
ms |
0.81
|
| CPU ResNet50-FP32-batch8 Throughput | 18.33 |
14.39
|
inferences/sec |
0.79
|
| CPU ResNet50-INT8-batch8 Latency | 22.37 |
29.79
|
ms |
0.75
|
| CPU ResNet50-INT8-batch8 Throughput | 46.62 |
39.91
|
inferences/sec |
0.86
|
| CPU SuperResolution-FP32-batch8 Latency | 58.42 |
72.02
|
ms |
0.81
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.87 |
19.33
|
inferences/sec |
0.93
|
| CPU SuperResolution-INT8-batch8 Latency | 21.34 |
28.92
|
ms |
0.74
|
| CPU SuperResolution-INT8-batch8 Throughput | 55.92 |
51.00
|
inferences/sec |
0.91
|
| GPU ResNet50-FP32-batch32 Throughput | 3.92 |
34.26
|
inferences/sec |
8.74
|
| GPU ResNet50-INT8-batch32 Throughput | 1.92 |
59.37
|
inferences/sec |
30.90
|
| GPU SuperResolution-FP32-batch32 Throughput | 6.59 |
30.92
|
inferences/sec |
4.69
|
| GPU SuperResolution-INT8-batch32 Throughput | 1.92 |
35.39
|
inferences/sec |
18.40
|
Industry Vertical Scores
| Energy | 1.63 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Convolution |
|
|||
| 20K/100 | 0.09 |
0.09
|
iterations/sec |
0.95
|
| Poisson |
|
|||
| Jacobi Rectangular Grid | 16.05 |
21.28
|
iterations/sec |
1.33
|
| Jacobi Square Grid | 6.19 |
7.55
|
iterations/sec |
1.22
|
| SRMP |
|
|||
| 2D | 19.45 |
23.27
|
sec |
0.84
|
| Viewport Graphics |
|
|||
| energy | 11.48 |
139.51
|
fps |
12.20
|
| WPCstorage |
|
|||
| energy | 1547.93 |
1444.91
|
points |
0.93
|
Industry Vertical Scores
| Financial Services | 0.83 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Options Pricing |
|
|||
| Monte Carlo | 35137.48 |
29362.26
|
options/sec |
0.84
|
| Black-Scholes | 3389.63 |
3088.18
|
Moptions/sec |
0.91
|
| Binomial | 79377.62 |
58901.67
|
options/sec |
0.74
|
Industry Vertical Scores
| Life Sciences | 1.79 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| LAMMPS |
|
|||
| LJ | 705.82 |
804.31
|
tau/day |
1.14
|
| CHAIN | 1190.35 |
1601.95
|
tau/day |
1.35
|
| EAM | 0.63 |
0.71
|
ns/day |
1.13
|
| CHUTE | 38.25 |
48.92
|
tau/day |
1.28
|
| RHODO | 0.26 |
0.26
|
ns/day |
1.00
|
| NAMD |
|
|||
| apoa1 | 45.38 |
43.17
|
ms/step |
1.05
|
| f1atpase | 130.50 |
131.60
|
ms/step |
0.99
|
| stmv | 448.57 |
421.93
|
ms/step |
1.06
|
| Rodinia Life Sciences |
|
|||
| Heart Wall | 0.69 |
0.70
|
fps |
1.02
|
| HotSpot | 8.55 |
8.69
|
sec |
0.98
|
| LavaMD | 0.07 |
0.07
|
iterations/sec |
0.99
|
| SRAD | 47.04 |
55.63
|
iterations/sec |
1.18
|
| Viewport Graphics |
|
|||
| medical | 9.63 |
120.19
|
fps |
12.50
|
| WPCstorage |
|
|||
| namd | 1250.61 |
1459.91
|
points |
1.17
|
Industry Vertical Scores
| Media & Entertainment | 1.86 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Blender |
|
|||
| Classroom | 281.72 |
97.96
|
sec |
2.88
|
| BMW27 | 43.82 |
45.95
|
sec |
0.95
|
| BMW1M | 17.74 |
17.82
|
sec |
1.00
|
| Island | 29.68 |
33.12
|
sec |
0.90
|
| HandBrake |
|
|||
| SVT-AV1 8K to 4K | 195.16 |
184.75
|
sec |
1.06
|
| x265 4K to 1080p | 38.36 |
42.78
|
sec |
0.90
|
| x265 4K to 4K | 107.73 |
110.37
|
sec |
0.98
|
| x264 1080p to 1080p | 49.98 |
14.19
|
sec |
3.52
|
| GPU H.265 4K to 4K | 169.65 |
232.94
|
fps |
1.37
|
| GPU H.265 4K to 1080p | 128.84 |
275.30
|
fps |
2.14
|
| LuxCoreRender |
|
|||
| DLSC | 2.46 |
2.80
|
Msamples/sec |
1.14
|
| Food | 1.84 |
2.06
|
Msamples/sec |
1.12
|
| Danish Mood | 2.29 |
2.06
|
Msamples/sec |
0.90
|
| Procedural Leaves | 1.10 |
1.14
|
Msamples/sec |
1.04
|
| Viewport Graphics |
|
|||
| 3dsmax | 15.96 |
177.76
|
fps |
11.10
|
| maya | 62.09 |
391.50
|
fps |
6.31
|
| WPCstorage |
|
|||
| 3dsmax | 3299.42 |
4069.25
|
points |
1.23
|
| handbrake | 1897.99 |
2644.89
|
points |
1.39
|
| maya | 2037.06 |
3374.88
|
points |
1.66
|
| MayaVenice | 472.63 |
827.22
|
points |
1.75
|
| MandE | 1625.72 |
1656.02
|
points |
1.02
|
Industry Vertical Scores
| Product Design | 1.65 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Autodesk Inventor |
|
|||
| Open Document | 4253.73 |
5966.00
|
ms |
0.71
|
| Create/Update Files | 4973.68 |
5331.00
|
ms |
0.93
|
| Rebuild | 10590.28 |
11591.00
|
ms |
0.91
|
| Render Style/Material | 628.78 |
2448.00
|
ms |
0.26
|
| Hidden Line Removal |
|
|||
| Palatov | 24.29 |
26.82
|
fps |
1.10
|
| MFEM |
|
|||
| Dynamic AMR | 227.39 |
234.39
|
sec |
0.97
|
| OpenFOAM |
|
|||
| XiFoam Solver | 803.27 |
153.83
|
sec |
5.22
|
| Rodinia CFD |
|
|||
| Pre-Euler | 138.14 |
198.97
|
iterations/sec |
1.44
|
| Viewport Graphics |
|
|||
| catia | 17.57 |
98.20
|
fps |
5.59
|
| creo | 48.42 |
202.93
|
fps |
4.19
|
| solidworks | 42.90 |
333.37
|
fps |
7.77
|
| WPCstorage |
|
|||
| ccx | 1398.45 |
2180.90
|
points |
1.56
|
| cfd | 1921.51 |
1989.18
|
points |
1.04
|
| icePack | 1543.34 |
1670.18
|
points |
1.08
|
| mcad | 2612.50 |
3294.75
|
points |
1.26
|
| proddev | 659.82 |
643.41
|
points |
0.97
|
Industry Vertical Scores
| Productivity & Development | 1.21 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| 7-Zip |
|
|||
| Decompression | 16.04 |
12.74
|
sec |
1.26
|
| Compression | 254.57 |
59.92
|
sec |
4.25
|
| LLVM Clang |
|
|||
| PyTorch | 562.76 |
528.59
|
sec |
1.06
|
| Octave |
|
|||
| obench | 1.20 |
1.04
|
sec/operation |
1.15
|
| benchmark2 | 0.11 |
0.10
|
sec/operation |
1.14
|
| Python 3 |
|
|||
| NumPy Create Matrix | 0.36 |
0.54
|
sec |
0.67
|
| NumPy Add Matrix | 4.44 |
4.14
|
sec |
1.07
|
| NumPy Multiply Matrix | 8.06 |
8.40
|
sec |
0.96
|
| NumPy Invert Matrix | 15.53 |
15.83
|
sec |
0.98
|
| NumPy Sin Matrix | 2.67 |
2.47
|
sec |
1.08
|
| Multi-Matrix | 65.50 |
61.79
|
sec |
1.06
|
| WPCstorage |
|
|||
| 7zip | 431.06 |
512.96
|
points |
1.19
|
| mozillaVS | 7708.43 |
6127.22
|
points |
0.80
|
Hardware Subsystem Scores
Hardware Subsystem
SPEC Ratio
4.60
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| HandBrake |
|
|||
| GPU H.265 4K to 4K | 169.65 |
232.94
|
fps |
1.37
|
| GPU H.265 4K to 1080p | 128.84 |
275.30
|
fps |
2.14
|
| ONNX Inference |
|
|||
| GPU ResNet50-FP32-batch32 Throughput | 3.92 |
34.26
|
inferences/sec |
8.74
|
| GPU ResNet50-INT8-batch32 Throughput | 1.92 |
59.37
|
inferences/sec |
30.90
|
| GPU SuperResolution-FP32-batch32 Throughput | 6.59 |
30.92
|
inferences/sec |
4.69
|
| GPU SuperResolution-INT8-batch32 Throughput | 1.92 |
35.39
|
inferences/sec |
18.40
|
1.17
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| 7-Zip |
|
|||
| Decompression | 16.04 |
12.74
|
sec |
1.26
|
| Compression | 254.57 |
59.92
|
sec |
4.25
|
| Autodesk Inventor |
|
|||
| Open Document | 4253.73 |
5966.00
|
ms |
0.71
|
| Create/Update Files | 4973.68 |
5331.00
|
ms |
0.93
|
| Rebuild | 10590.28 |
11591.00
|
ms |
0.91
|
| Render Style/Material | 628.78 |
2448.00
|
ms |
0.26
|
| Blender |
|
|||
| Classroom | 281.72 |
97.96
|
sec |
2.88
|
| BMW27 | 43.82 |
45.95
|
sec |
0.95
|
| BMW1M | 17.74 |
17.82
|
sec |
1.00
|
| Island | 29.68 |
33.12
|
sec |
0.90
|
| Convolution |
|
|||
| 20K/100 | 0.09 |
0.09
|
iterations/sec |
0.95
|
| Data Science |
|
|||
| Pandas | 131.99 |
110.04
|
sec |
1.20
|
| Scikit-learn | 449.17 |
331.14
|
sec |
1.36
|
| XGBoost | 91.50 |
57.65
|
sec |
1.59
|
| HandBrake |
|
|||
| SVT-AV1 8K to 4K | 195.16 |
184.75
|
sec |
1.06
|
| x265 4K to 1080p | 38.36 |
42.78
|
sec |
0.90
|
| x265 4K to 4K | 107.73 |
110.37
|
sec |
0.98
|
| x264 1080p to 1080p | 49.98 |
14.19
|
sec |
3.52
|
| Hidden Line Removal |
|
|||
| Palatov | 24.29 |
26.82
|
fps |
1.10
|
| LAMMPS |
|
|||
| LJ | 705.82 |
804.31
|
tau/day |
1.14
|
| CHAIN | 1190.35 |
1601.95
|
tau/day |
1.35
|
| EAM | 0.63 |
0.71
|
ns/day |
1.13
|
| CHUTE | 38.25 |
48.92
|
tau/day |
1.28
|
| RHODO | 0.26 |
0.26
|
ns/day |
1.00
|
| LLVM Clang |
|
|||
| PyTorch | 562.76 |
528.59
|
sec |
1.06
|
| LuxCoreRender |
|
|||
| DLSC | 2.46 |
2.80
|
Msamples/sec |
1.14
|
| Food | 1.84 |
2.06
|
Msamples/sec |
1.12
|
| Danish Mood | 2.29 |
2.06
|
Msamples/sec |
0.90
|
| Procedural Leaves | 1.10 |
1.14
|
Msamples/sec |
1.04
|
| MFEM |
|
|||
| Dynamic AMR | 227.39 |
234.39
|
sec |
0.97
|
| NAMD |
|
|||
| apoa1 | 45.38 |
43.17
|
ms/step |
1.05
|
| f1atpase | 130.50 |
131.60
|
ms/step |
0.99
|
| stmv | 448.57 |
421.93
|
ms/step |
1.06
|
| Octave |
|
|||
| obench | 1.20 |
1.04
|
sec/operation |
1.15
|
| benchmark2 | 0.11 |
0.10
|
sec/operation |
1.14
|
| ONNX Inference |
|
|||
| CPU ResNet50-FP32-batch8 Latency | 63.72 |
78.94
|
ms |
0.81
|
| CPU ResNet50-FP32-batch8 Throughput | 18.33 |
14.39
|
inferences/sec |
0.79
|
| CPU ResNet50-INT8-batch8 Latency | 22.37 |
29.79
|
ms |
0.75
|
| CPU ResNet50-INT8-batch8 Throughput | 46.62 |
39.91
|
inferences/sec |
0.86
|
| CPU SuperResolution-FP32-batch8 Latency | 58.42 |
72.02
|
ms |
0.81
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.87 |
19.33
|
inferences/sec |
0.93
|
| CPU SuperResolution-INT8-batch8 Latency | 21.34 |
28.92
|
ms |
0.74
|
| CPU SuperResolution-INT8-batch8 Throughput | 55.92 |
51.00
|
inferences/sec |
0.91
|
| OpenFOAM |
|
|||
| XiFoam Solver | 803.27 |
153.83
|
sec |
5.22
|
| Options Pricing |
|
|||
| Monte Carlo | 35137.48 |
29362.26
|
options/sec |
0.84
|
| Black-Scholes | 3389.63 |
3088.18
|
Moptions/sec |
0.91
|
| Binomial | 79377.62 |
58901.67
|
options/sec |
0.74
|
| Poisson |
|
|||
| Jacobi Rectangular Grid | 16.05 |
21.28
|
iterations/sec |
1.33
|
| Jacobi Square Grid | 6.19 |
7.55
|
iterations/sec |
1.22
|
| Python 3 |
|
|||
| NumPy Create Matrix | 0.36 |
0.54
|
sec |
0.67
|
| NumPy Add Matrix | 4.44 |
4.14
|
sec |
1.07
|
| NumPy Multiply Matrix | 8.06 |
8.40
|
sec |
0.96
|
| NumPy Invert Matrix | 15.53 |
15.83
|
sec |
0.98
|
| NumPy Sin Matrix | 2.67 |
2.47
|
sec |
1.08
|
| Multi-Matrix | 65.50 |
61.79
|
sec |
1.06
|
| Rodinia CFD |
|
|||
| Pre-Euler | 138.14 |
198.97
|
iterations/sec |
1.44
|
| Rodinia Life Sciences |
|
|||
| Heart Wall | 0.69 |
0.70
|
fps |
1.02
|
| HotSpot | 8.55 |
8.69
|
sec |
0.98
|
| LavaMD | 0.07 |
0.07
|
iterations/sec |
0.99
|
| SRAD | 47.04 |
55.63
|
iterations/sec |
1.18
|
| SRMP |
|
|||
| 2D | 19.45 |
23.27
|
sec |
0.84
|
7.91
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Viewport Graphics |
|
|||
| 3dsmax | 15.96 |
177.76
|
fps |
11.10
|
| catia | 17.57 |
98.20
|
fps |
5.59
|
| creo | 48.42 |
202.93
|
fps |
4.19
|
| energy | 11.48 |
139.51
|
fps |
12.20
|
| maya | 62.09 |
391.50
|
fps |
6.31
|
| medical | 9.63 |
120.19
|
fps |
12.50
|
| solidworks | 42.90 |
333.37
|
fps |
7.77
|
1.19
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| WPCstorage |
|
|||
| 3dsmax | 3299.42 |
4069.25
|
points |
1.23
|
| 7zip | 431.06 |
512.96
|
points |
1.19
|
| ccx | 1398.45 |
2180.90
|
points |
1.56
|
| cfd | 1921.51 |
1989.18
|
points |
1.04
|
| energy | 1547.93 |
1444.91
|
points |
0.93
|
| handbrake | 1897.99 |
2644.89
|
points |
1.39
|
| icePack | 1543.34 |
1670.18
|
points |
1.08
|
| maya | 2037.06 |
3374.88
|
points |
1.66
|
| MayaVenice | 472.63 |
827.22
|
points |
1.75
|
| MandE | 1625.72 |
1656.02
|
points |
1.02
|
| mcad | 2612.50 |
3294.75
|
points |
1.26
|
| mozillaVS | 7708.43 |
6127.22
|
points |
0.80
|
| namd | 1250.61 |
1459.91
|
points |
1.17
|
| proddev | 659.82 |
643.41
|
points |
0.97
|
Workload Scores
| Workload | Time Stamp | Execution Time | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|---|---|
| 7-Zip | Nov 20, 2024, 9:41:49 PM EST |
2.95
|
||||
| Decompression | 12.74 sec | 16.04 |
12.74
|
sec |
1.26
|
|
| Compression | 59.92 sec | 254.57 |
59.92
|
sec |
4.25
|
|
| Autodesk Inventor | Nov 20, 2024, 9:43:05 PM EST |
0.63
|
||||
| Open Document | 6.15 sec | 4253.73 |
5966.00
|
ms |
0.71
|
|
| Create/Update Files | 7.03 sec | 4973.68 |
5331.00
|
ms |
0.93
|
|
| Rebuild | 11.78 sec | 10590.28 |
11591.00
|
ms |
0.91
|
|
| Render Style/Material | 2.63 sec | 628.78 |
2448.00
|
ms |
0.26
|
|
| Blender | Nov 20, 2024, 9:44:06 PM EST |
1.25
|
||||
| Classroom | 97.96 sec | 281.72 |
97.96
|
sec |
2.88
|
|
| BMW27 | 45.95 sec | 43.82 |
45.95
|
sec |
0.95
|
|
| BMW1M | 17.82 sec | 17.74 |
17.82
|
sec |
1.00
|
|
| Island | 33.12 sec | 29.68 |
33.12
|
sec |
0.90
|
|
| Convolution | Nov 20, 2024, 9:47:25 PM EST |
0.95
|
||||
| 20K/100 | 36.71 sec | 0.09 |
0.09
|
iterations/sec |
0.95
|
|
| Data Science | Nov 20, 2024, 9:48:02 PM EST |
1.37
|
||||
| Pandas | 141.06 sec | 131.99 |
110.04
|
sec |
1.20
|
|
| Scikit-learn | 335.13 sec | 449.17 |
331.14
|
sec |
1.36
|
|
| XGBoost | 77.74 sec | 91.50 |
57.65
|
sec |
1.59
|
|
| HandBrake | Nov 20, 2024, 9:57:28 PM EST |
1.46
|
||||
| SVT-AV1 8K to 4K | 184.75 sec | 195.16 |
184.75
|
sec |
1.06
|
|
| x265 4K to 1080p | 45.18 sec | 38.36 |
42.78
|
sec |
0.90
|
|
| x265 4K to 4K | 112.92 sec | 107.73 |
110.37
|
sec |
0.98
|
|
| x264 1080p to 1080p | 14.19 sec | 49.98 |
14.19
|
sec |
3.52
|
|
| GPU H.265 4K to 4K | 66.69 sec | 169.65 |
115.93
|
fps |
0.68
|
|
| GPU H.265 4K to 4K | 57.69 sec | 169.65 |
232.94
|
fps |
1.37
|
|
| GPU H.265 4K to 1080p | 211.54 sec | 128.84 |
253.35
|
fps |
1.97
|
|
| GPU H.265 4K to 1080p | 220.46 sec | 128.84 |
275.30
|
fps |
2.14
|
|
| Hidden Line Removal | Nov 20, 2024, 10:12:48 PM EST |
1.10
|
||||
| Palatov | 16.95 sec | 24.29 |
26.82
|
fps |
1.10
|
|
| Palatov | 17.21 sec | 24.29 |
23.64
|
fps |
0.97
|
|
| LAMMPS | Nov 20, 2024, 10:13:23 PM EST |
1.17
|
||||
| LJ | 18.58 sec | 705.82 |
804.31
|
tau/day |
1.14
|
|
| CHAIN | 14.44 sec | 1190.35 |
1601.95
|
tau/day |
1.35
|
|
| EAM | 19.47 sec | 0.63 |
0.71
|
ns/day |
1.13
|
|
| CHUTE | 8.49 sec | 38.25 |
48.92
|
tau/day |
1.28
|
|
| RHODO | 9.67 sec | 0.26 |
0.26
|
ns/day |
1.00
|
|
| LLVM Clang | Nov 20, 2024, 10:14:33 PM EST |
1.06
|
||||
| PyTorch | 545.66 sec | 562.76 |
528.59
|
sec |
1.06
|
|
| LuxCoreRender | Nov 20, 2024, 10:24:29 PM EST |
1.05
|
||||
| DLSC | 17.68 sec | 2.46 |
2.80
|
Msamples/sec |
1.14
|
|
| Food | 25.58 sec | 1.84 |
2.06
|
Msamples/sec |
1.12
|
|
| Danish Mood | 72.48 sec | 2.29 |
2.06
|
Msamples/sec |
0.90
|
|
| Procedural Leaves | 47.14 sec | 1.10 |
1.14
|
Msamples/sec |
1.04
|
|
| MFEM | Nov 20, 2024, 10:27:12 PM EST |
0.97
|
||||
| Dynamic AMR | 234.39 sec | 227.39 |
234.39
|
sec |
0.97
|
|
| NAMD | Nov 20, 2024, 10:31:07 PM EST |
1.03
|
||||
| apoa1 | 13.02 sec | 45.38 |
43.17
|
ms/step |
1.05
|
|
| f1atpase | 21.43 sec | 130.50 |
131.60
|
ms/step |
0.99
|
|
| stmv | 48.72 sec | 448.57 |
421.93
|
ms/step |
1.06
|
|
| Octave | Nov 20, 2024, 10:32:30 PM EST |
1.14
|
||||
| obench | 46.95 sec | 1.20 |
1.04
|
sec/operation |
1.15
|
|
| benchmark2 | 10.77 sec | 0.11 |
0.10
|
sec/operation |
1.14
|
|
| ONNX Inference | Nov 20, 2024, 10:33:36 PM EST |
2.03
|
||||
| CPU ResNet50-FP32-batch8 Latency | 20.42 sec | 63.72 |
78.94
|
ms |
0.81
|
|
| CPU ResNet50-FP32-batch8 Throughput | 21.21 sec | 18.33 |
14.39
|
inferences/sec |
0.79
|
|
| CPU ResNet50-FP32-batch8 Throughput | 22.08 sec | 18.33 |
13.20
|
inferences/sec |
0.72
|
|
| CPU ResNet50-INT8-batch8 Latency | 20.17 sec | 22.37 |
29.79
|
ms |
0.75
|
|
| CPU ResNet50-INT8-batch8 Throughput | 20.52 sec | 46.62 |
39.91
|
inferences/sec |
0.86
|
|
| CPU ResNet50-INT8-batch8 Throughput | 20.74 sec | 46.62 |
37.40
|
inferences/sec |
0.80
|
|
| CPU SuperResolution-FP32-batch8 Latency | 20.16 sec | 58.42 |
72.02
|
ms |
0.81
|
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.86 sec | 20.87 |
19.33
|
inferences/sec |
0.93
|
|
| CPU SuperResolution-FP32-batch8 Throughput | 21.48 sec | 20.87 |
16.89
|
inferences/sec |
0.81
|
|
| CPU SuperResolution-INT8-batch8 Latency | 20.11 sec | 21.34 |
28.92
|
ms |
0.74
|
|
| CPU SuperResolution-INT8-batch8 Throughput | 20.37 sec | 55.92 |
51.00
|
inferences/sec |
0.91
|
|
| CPU SuperResolution-INT8-batch8 Throughput | 20.64 sec | 55.92 |
43.66
|
inferences/sec |
0.78
|
|
| GPU ResNet50-FP32-batch32 Throughput | 22.18 sec | 3.92 |
34.11
|
inferences/sec |
8.70
|
|
| GPU ResNet50-FP32-batch32 Throughput | 20.65 sec | 3.92 |
34.26
|
inferences/sec |
8.74
|
|
| GPU ResNet50-INT8-batch32 Throughput | 20.63 sec | 1.92 |
58.11
|
inferences/sec |
30.30
|
|
| GPU ResNet50-INT8-batch32 Throughput | 20.72 sec | 1.92 |
59.37
|
inferences/sec |
30.90
|
|
| GPU SuperResolution-FP32-batch32 Throughput | 21.55 sec | 6.59 |
30.78
|
inferences/sec |
4.67
|
|
| GPU SuperResolution-FP32-batch32 Throughput | 21.41 sec | 6.59 |
30.92
|
inferences/sec |
4.69
|
|
| GPU SuperResolution-INT8-batch32 Throughput | 21.48 sec | 1.92 |
35.39
|
inferences/sec |
18.40
|
|
| GPU SuperResolution-INT8-batch32 Throughput | 21.37 sec | 1.92 |
35.23
|
inferences/sec |
18.30
|
|
| OpenFOAM | Nov 20, 2024, 10:40:36 PM EST |
5.22
|
||||
| XiFoam Solver | 163.11 sec | 803.27 |
153.83
|
sec |
5.22
|
|
| XiFoam Solver | 192.00 sec | 803.27 |
182.32
|
sec |
4.41
|
|
| Options Pricing | Nov 20, 2024, 10:46:35 PM EST |
0.83
|
||||
| Monte Carlo | 35.78 sec | 35137.48 |
29362.26
|
options/sec |
0.84
|
|
| Black-Scholes | 22.50 sec | 3389.63 |
3088.18
|
Moptions/sec |
0.91
|
|
| Binomial | 17.86 sec | 79377.62 |
58901.67
|
options/sec |
0.74
|
|
| Poisson | Nov 20, 2024, 10:47:51 PM EST |
1.27
|
||||
| Jacobi Rectangular Grid | 10.08 sec | 16.05 |
21.28
|
iterations/sec |
1.33
|
|
| Jacobi Rectangular Grid | 10.05 sec | 16.05 |
19.84
|
iterations/sec |
1.24
|
|
| Jacobi Square Grid | 10.22 sec | 6.19 |
7.55
|
iterations/sec |
1.22
|
|
| Jacobi Square Grid | 10.14 sec | 6.19 |
7.01
|
iterations/sec |
1.13
|
|
| Python 3 | Nov 20, 2024, 10:48:31 PM EST |
1.00
|
||||
| NumPy Create Matrix | 8.48 sec | 0.36 |
0.54
|
sec |
0.67
|
|
| NumPy Add Matrix | 4.80 sec | 4.44 |
4.14
|
sec |
1.07
|
|
| NumPy Multiply Matrix | 9.05 sec | 8.06 |
8.40
|
sec |
0.96
|
|
| NumPy Invert Matrix | 16.50 sec | 15.53 |
15.83
|
sec |
0.98
|
|
| NumPy Sin Matrix | 3.13 sec | 2.67 |
2.47
|
sec |
1.08
|
|
| Multi-Matrix | 62.46 sec | 65.50 |
61.79
|
sec |
1.06
|
|
| Rodinia CFD | Nov 20, 2024, 10:50:25 PM EST |
1.44
|
||||
| Pre-Euler | 33.03 sec | 138.14 |
198.97
|
iterations/sec |
1.44
|
|
| Rodinia Life Sciences | Nov 20, 2024, 10:50:58 PM EST |
1.04
|
||||
| Heart Wall | 11.55 sec | 0.69 |
0.70
|
fps |
1.02
|
|
| HotSpot | 9.74 sec | 8.55 |
8.69
|
sec |
0.98
|
|
| LavaMD | 14.87 sec | 0.07 |
0.07
|
iterations/sec |
0.99
|
|
| SRAD | 10.22 sec | 47.04 |
55.63
|
iterations/sec |
1.18
|
|
| SRMP | Nov 20, 2024, 10:51:45 PM EST |
0.84
|
||||
| 2D | 23.69 sec | 19.45 |
23.27
|
sec |
0.84
|
|
| Viewport Graphics | Nov 20, 2024, 10:52:08 PM EST |
7.91
|
||||
| 3dsmax | 158.78 sec | 15.96 |
177.76
|
fps |
11.10
|
|
| catia | 135.41 sec | 17.57 |
98.20
|
fps |
5.59
|
|
| creo | 226.42 sec | 48.42 |
202.93
|
fps |
4.19
|
|
| energy | 79.18 sec | 11.48 |
139.51
|
fps |
12.20
|
|
| maya | 141.07 sec | 62.09 |
391.50
|
fps |
6.31
|
|
| medical | 75.31 sec | 9.63 |
120.19
|
fps |
12.50
|
|
| solidworks | 83.01 sec | 42.90 |
333.37
|
fps |
7.77
|
|
| WPCstorage | Nov 20, 2024, 11:08:10 PM EST |
1.19
|
||||
| 3dsmax | 51.76 sec | 3299.42 |
4069.25
|
points |
1.23
|
|
| 7zip | 55.13 sec | 431.06 |
512.96
|
points |
1.19
|
|
| ccx | 11.61 sec | 1398.45 |
2180.90
|
points |
1.56
|
|
| cfd | 12.25 sec | 1921.51 |
1989.18
|
points |
1.04
|
|
| energy | 21.58 sec | 1547.93 |
1444.91
|
points |
0.93
|
|
| handbrake | 15.49 sec | 1897.99 |
2644.89
|
points |
1.39
|
|
| icePack | 54.50 sec | 1543.34 |
1670.18
|
points |
1.08
|
|
| maya | 43.23 sec | 2037.06 |
3374.88
|
points |
1.66
|
|
| MayaVenice | 24.83 sec | 472.63 |
827.22
|
points |
1.75
|
|
| MandE | 20.67 sec | 1625.72 |
1656.02
|
points |
1.02
|
|
| mcad | 59.27 sec | 2612.50 |
3294.75
|
points |
1.26
|
|
| mozillaVS | 30.00 sec | 7708.43 |
6127.22
|
points |
0.80
|
|
| namd | 16.43 sec | 1250.61 |
1459.91
|
points |
1.17
|
|
| proddev | 18.21 sec | 659.82 |
643.41
|
points |
0.97
|
System Configuration Details
MOTHERBOARD
Name: 21FWZB12USModel: Lenovo ThinkPad P1 Gen 6
Version: 21KWZC4AUS
Manufacturer: LENOVO
Serial Number: W1CG3480A53
BIOS: LENOVO N3ZET27W (1.14 )
BIOS Version: LENOVO - 10140 (2023-09-13)
PROCESSOR
CPU #1: 13th Gen Intel(R) Core(TM) i9-13900H (2600MHz / 14C / 20T)
MEMORY
BANK 0/1 (Controller0-ChannelA/B-DIMM0): SK Hynix HMCG88AGBAA092N (32.00 GB / 5600 MHz / DDR5)BANK 0/1 (Controller1-ChannelA/B-DIMM0): SK Hynix HMCG88AGBAA092N (32.00 GB / 5600 MHz / DDR5)
Total Memory: 64.00 GB
STORAGE
Disk #1: KXG8AZN84T09 LA KIOXIA (3815.44 GB - SCSI)Partition 1: GPT: System (0.25 GB)
Partition 2: GPT: Basic Data (3813.22 GB)
Partition 3: GPT: Unknown (1.95 GB)
Available Volumes
C: (Windows): NTFS (3715.55 GB of 3813.22 GB Available)
NETWORK
Adapter #1: Bluetooth Device (Personal Area Network)Type: Ethernet 802.3 | MAC: 08:9D:F4:79:AB:C0 | Speed: Not Connected
Adapter #2: Intel(R) Wi-Fi 6E AX211 160MHz
Type: Ethernet 802.3 | MAC: 08:9D:F4:79:AB:BC | Speed: Not Connected
GRAPHICS
Adapter #1: Intel(R) Iris(R) Xe GraphicsVideo Memory: 31.96 GB
Current Resolution: 3840x2400 @ 60 Hz (32-bit Color)
Driver Version: 32.0.101.5972 (2024-08-18)
Adapter #2: NVIDIA RTX 5000 Ada Generation Laptop GPU
Video Memory: 15.99 GB
Current Resolution: Unknown
Driver Version: 31.0.15.3878 (2024-06-09)
DISPLAY
Display #1: LENOVO GROUP LIMITED Internal Display 15.9" (3840x2400)Model: 4146 | S/N: None | Connector: Internal Display (Digital)
Windows Screens
Screen 1: 1920x1200 @ 32 bpp
BATTERY
Battery #1 (Front): P/N: 5B11K07737 | Mfg: Sunwoda | Charge Level: 99%
OPERATING SYSTEM
Name: Microsoft Windows 11 Pro 64-bitVersion: 10.0.26100.2033 (Release 2009)
Installation Date: 2024-11-08
Free Memory: 55.50 GB (Physical) | 58.49 GB (Virtual) | 4.00 GB (Paging)
Screensaver: Disabled
Visual Effects Setting: Let Windows Choose
Virtualization Based Security (VBS): Running
Active Power Plan: Balanced (381b4222-f694-41f0-9685-ff5bb260df2e)