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 | HP |
| Model | HP ZBook Power 16 inch G11 A Mobile Workstation PC |
| CPU | AMD Ryzen 9 PRO 8945HS w/ Radeon 780M Graphics |
| Memory | 64.00 GB @ 5600 MHz |
| GPU | 1x NVIDIA RTX 3000 Ada Generation Laptop GPU 1x AMD Radeon(TM) Graphics |
| Display | Internal Display 16.3" (1920x1200) |
| Storage | SAMSUNG MZVL22T0HBLB-00BH1 1907.73 GB - SCSI |
| OS | Microsoft Windows 11 Pro (22631) |
Submission Details
| Result Date | Thu Nov 21 2024 10:51:42 GMT-0800 (Pacific Standard Time) |
| Submitter Company | |
| Submitter Name | |
| Submitter Comments |
Industry Vertical Scores
AI & Machine Learning |
1.46 |
Energy |
1.28 |
Financial Services |
0.92 |
Life Sciences |
1.43 |
Media & Entertainment |
1.35 |
Product Design |
1.41 |
Productivity & Development |
1.07 |
Hardware Subsystem Scores
| CPU | 1.05 |
| Accelerator | 3.26 |
| Graphics | 4.71 |
| Storage | 0.91 |
| Workload | SPEC Ratio |
|---|---|
| 7-Zip | 2.35 |
| Autodesk Inventor | 0.94 |
| Blender | 1.15 |
| Convolution | 0.85 |
| Data Science | 1.09 |
| HandBrake | 1.05 |
| Hidden Line Removal | 0.92 |
| LAMMPS | 1.02 |
| LLVM Clang | 0.79 |
| LuxCoreRender | 0.92 |
| MFEM | 0.88 |
| NAMD | 0.82 |
| Octave | 1.16 |
| ONNX Inference | 1.95 |
| OpenFOAM | 4.37 |
| Options Pricing | 0.93 |
| Poisson | 1.13 |
| Python 3 | 0.88 |
| Rodinia CFD | 1.04 |
| Rodinia Life Sciences | 0.84 |
| SRMP | 0.77 |
| Viewport Graphics | 4.71 |
| WPCstorage | 0.91 |
Industry Vertical Scores
| AI & Machine Learning | 1.46 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Data Science |
|
|||
| Pandas | 131.99 |
126.57
|
sec |
1.04
|
| Scikit-learn | 449.17 |
501.60
|
sec |
0.90
|
| XGBoost | 91.50 |
65.32
|
sec |
1.40
|
| ONNX Inference |
|
|||
| CPU ResNet50-FP32-batch8 Latency | 63.72 |
69.50
|
ms |
0.92
|
| CPU ResNet50-FP32-batch8 Throughput | 18.33 |
14.24
|
inferences/sec |
0.78
|
| CPU ResNet50-INT8-batch8 Latency | 22.37 |
22.04
|
ms |
1.01
|
| CPU ResNet50-INT8-batch8 Throughput | 46.62 |
47.84
|
inferences/sec |
1.03
|
| CPU SuperResolution-FP32-batch8 Latency | 58.42 |
59.81
|
ms |
0.98
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.87 |
18.75
|
inferences/sec |
0.90
|
| CPU SuperResolution-INT8-batch8 Latency | 21.34 |
23.34
|
ms |
0.91
|
| CPU SuperResolution-INT8-batch8 Throughput | 55.92 |
51.67
|
inferences/sec |
0.92
|
| GPU ResNet50-FP32-batch32 Throughput | 3.92 |
18.52
|
inferences/sec |
4.72
|
| GPU ResNet50-INT8-batch32 Throughput | 1.92 |
40.51
|
inferences/sec |
21.10
|
| GPU SuperResolution-FP32-batch32 Throughput | 6.59 |
24.82
|
inferences/sec |
3.77
|
| GPU SuperResolution-INT8-batch32 Throughput | 1.92 |
27.79
|
inferences/sec |
14.50
|
Industry Vertical Scores
| Energy | 1.28 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Convolution |
|
|||
| 20K/100 | 0.09 |
0.08
|
iterations/sec |
0.85
|
| Poisson |
|
|||
| Jacobi Rectangular Grid | 16.05 |
18.11
|
iterations/sec |
1.13
|
| Jacobi Square Grid | 6.19 |
7.08
|
iterations/sec |
1.14
|
| SRMP |
|
|||
| 2D | 19.45 |
25.14
|
sec |
0.77
|
| Viewport Graphics |
|
|||
| energy | 11.48 |
73.91
|
fps |
6.44
|
| WPCstorage |
|
|||
| energy | 1547.93 |
1119.54
|
points |
0.72
|
Industry Vertical Scores
| Financial Services | 0.92 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Options Pricing |
|
|||
| Monte Carlo | 35137.48 |
36451.07
|
options/sec |
1.04
|
| Black-Scholes | 3389.63 |
3316.23
|
Moptions/sec |
0.98
|
| Binomial | 79377.62 |
61793.50
|
options/sec |
0.78
|
Industry Vertical Scores
| Life Sciences | 1.43 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| LAMMPS |
|
|||
| LJ | 705.82 |
782.36
|
tau/day |
1.11
|
| CHAIN | 1190.35 |
1342.27
|
tau/day |
1.13
|
| EAM | 0.63 |
0.66
|
ns/day |
1.04
|
| CHUTE | 38.25 |
36.19
|
tau/day |
0.95
|
| RHODO | 0.26 |
0.24
|
ns/day |
0.92
|
| NAMD |
|
|||
| apoa1 | 45.38 |
54.65
|
ms/step |
0.83
|
| f1atpase | 130.50 |
164.51
|
ms/step |
0.79
|
| stmv | 448.57 |
532.74
|
ms/step |
0.84
|
| Rodinia Life Sciences |
|
|||
| Heart Wall | 0.69 |
0.67
|
fps |
0.96
|
| HotSpot | 8.55 |
16.45
|
sec |
0.52
|
| LavaMD | 0.07 |
0.07
|
iterations/sec |
1.00
|
| SRAD | 47.04 |
46.92
|
iterations/sec |
1.00
|
| Viewport Graphics |
|
|||
| medical | 9.63 |
84.68
|
fps |
8.79
|
| WPCstorage |
|
|||
| namd | 1250.61 |
1182.26
|
points |
0.94
|
Industry Vertical Scores
| Media & Entertainment | 1.35 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Blender |
|
|||
| Classroom | 281.72 |
109.19
|
sec |
2.58
|
| BMW27 | 43.82 |
50.19
|
sec |
0.87
|
| BMW1M | 17.74 |
19.00
|
sec |
0.93
|
| Island | 29.68 |
36.00
|
sec |
0.82
|
| HandBrake |
|
|||
| SVT-AV1 8K to 4K | 195.16 |
242.55
|
sec |
0.81
|
| x265 4K to 1080p | 38.36 |
50.20
|
sec |
0.76
|
| x265 4K to 4K | 107.73 |
174.91
|
sec |
0.62
|
| x264 1080p to 1080p | 49.98 |
21.75
|
sec |
2.30
|
| GPU H.265 4K to 4K | 169.65 |
155.24
|
fps |
0.92
|
| GPU H.265 4K to 1080p | 128.84 |
216.95
|
fps |
1.68
|
| LuxCoreRender |
|
|||
| DLSC | 2.46 |
2.36
|
Msamples/sec |
0.96
|
| Food | 1.84 |
1.76
|
Msamples/sec |
0.96
|
| Danish Mood | 2.29 |
1.88
|
Msamples/sec |
0.82
|
| Procedural Leaves | 1.10 |
1.04
|
Msamples/sec |
0.94
|
| Viewport Graphics |
|
|||
| 3dsmax | 15.96 |
76.64
|
fps |
4.80
|
| maya | 62.09 |
249.49
|
fps |
4.02
|
| WPCstorage |
|
|||
| 3dsmax | 3299.42 |
3496.77
|
points |
1.06
|
| handbrake | 1897.99 |
2018.47
|
points |
1.06
|
| maya | 2037.06 |
1753.70
|
points |
0.86
|
| MayaVenice | 472.63 |
385.81
|
points |
0.82
|
| MandE | 1625.72 |
1388.44
|
points |
0.85
|
Industry Vertical Scores
| Product Design | 1.41 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Autodesk Inventor |
|
|||
| Open Document | 4253.73 |
4646.00
|
ms |
0.92
|
| Create/Update Files | 4973.68 |
5313.00
|
ms |
0.94
|
| Rebuild | 10590.28 |
10657.00
|
ms |
0.99
|
| Render Style/Material | 628.78 |
673.00
|
ms |
0.93
|
| Hidden Line Removal |
|
|||
| Palatov | 24.29 |
22.36
|
fps |
0.92
|
| MFEM |
|
|||
| Dynamic AMR | 227.39 |
259.18
|
sec |
0.88
|
| OpenFOAM |
|
|||
| XiFoam Solver | 803.27 |
183.78
|
sec |
4.37
|
| Rodinia CFD |
|
|||
| Pre-Euler | 138.14 |
143.10
|
iterations/sec |
1.04
|
| Viewport Graphics |
|
|||
| catia | 17.57 |
62.09
|
fps |
3.53
|
| creo | 48.42 |
134.54
|
fps |
2.78
|
| solidworks | 42.90 |
206.70
|
fps |
4.82
|
| WPCstorage |
|
|||
| ccx | 1398.45 |
1654.05
|
points |
1.18
|
| cfd | 1921.51 |
1375.70
|
points |
0.72
|
| icePack | 1543.34 |
1295.89
|
points |
0.84
|
| mcad | 2612.50 |
3250.83
|
points |
1.24
|
| proddev | 659.82 |
452.78
|
points |
0.69
|
Industry Vertical Scores
| Productivity & Development | 1.07 | |||
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| 7-Zip |
|
|||
| Decompression | 16.04 |
17.48
|
sec |
0.92
|
| Compression | 254.57 |
72.31
|
sec |
3.52
|
| LLVM Clang |
|
|||
| PyTorch | 562.76 |
714.83
|
sec |
0.79
|
| Octave |
|
|||
| obench | 1.20 |
1.01
|
sec/operation |
1.19
|
| benchmark2 | 0.11 |
0.10
|
sec/operation |
1.13
|
| Python 3 |
|
|||
| NumPy Create Matrix | 0.36 |
0.33
|
sec |
1.09
|
| NumPy Add Matrix | 4.44 |
4.77
|
sec |
0.93
|
| NumPy Multiply Matrix | 8.06 |
10.47
|
sec |
0.77
|
| NumPy Invert Matrix | 15.53 |
20.22
|
sec |
0.77
|
| NumPy Sin Matrix | 2.67 |
2.80
|
sec |
0.95
|
| Multi-Matrix | 65.50 |
76.14
|
sec |
0.86
|
| WPCstorage |
|
|||
| 7zip | 431.06 |
498.45
|
points |
1.16
|
| mozillaVS | 7708.43 |
6412.59
|
points |
0.83
|
Hardware Subsystem Scores
Hardware Subsystem
SPEC Ratio
3.26
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| HandBrake |
|
|||
| GPU H.265 4K to 4K | 169.65 |
155.24
|
fps |
0.92
|
| GPU H.265 4K to 1080p | 128.84 |
216.95
|
fps |
1.68
|
| ONNX Inference |
|
|||
| GPU ResNet50-FP32-batch32 Throughput | 3.92 |
18.52
|
inferences/sec |
4.72
|
| GPU ResNet50-INT8-batch32 Throughput | 1.92 |
40.51
|
inferences/sec |
21.10
|
| GPU SuperResolution-FP32-batch32 Throughput | 6.59 |
24.82
|
inferences/sec |
3.77
|
| GPU SuperResolution-INT8-batch32 Throughput | 1.92 |
27.79
|
inferences/sec |
14.50
|
1.05
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| 7-Zip |
|
|||
| Decompression | 16.04 |
17.48
|
sec |
0.92
|
| Compression | 254.57 |
72.31
|
sec |
3.52
|
| Autodesk Inventor |
|
|||
| Open Document | 4253.73 |
4646.00
|
ms |
0.92
|
| Create/Update Files | 4973.68 |
5313.00
|
ms |
0.94
|
| Rebuild | 10590.28 |
10657.00
|
ms |
0.99
|
| Render Style/Material | 628.78 |
673.00
|
ms |
0.93
|
| Blender |
|
|||
| Classroom | 281.72 |
109.19
|
sec |
2.58
|
| BMW27 | 43.82 |
50.19
|
sec |
0.87
|
| BMW1M | 17.74 |
19.00
|
sec |
0.93
|
| Island | 29.68 |
36.00
|
sec |
0.82
|
| Convolution |
|
|||
| 20K/100 | 0.09 |
0.08
|
iterations/sec |
0.85
|
| Data Science |
|
|||
| Pandas | 131.99 |
126.57
|
sec |
1.04
|
| Scikit-learn | 449.17 |
501.60
|
sec |
0.90
|
| XGBoost | 91.50 |
65.32
|
sec |
1.40
|
| HandBrake |
|
|||
| SVT-AV1 8K to 4K | 195.16 |
242.55
|
sec |
0.81
|
| x265 4K to 1080p | 38.36 |
50.20
|
sec |
0.76
|
| x265 4K to 4K | 107.73 |
174.91
|
sec |
0.62
|
| x264 1080p to 1080p | 49.98 |
21.75
|
sec |
2.30
|
| Hidden Line Removal |
|
|||
| Palatov | 24.29 |
22.36
|
fps |
0.92
|
| LAMMPS |
|
|||
| LJ | 705.82 |
782.36
|
tau/day |
1.11
|
| CHAIN | 1190.35 |
1342.27
|
tau/day |
1.13
|
| EAM | 0.63 |
0.66
|
ns/day |
1.04
|
| CHUTE | 38.25 |
36.19
|
tau/day |
0.95
|
| RHODO | 0.26 |
0.24
|
ns/day |
0.92
|
| LLVM Clang |
|
|||
| PyTorch | 562.76 |
714.83
|
sec |
0.79
|
| LuxCoreRender |
|
|||
| DLSC | 2.46 |
2.36
|
Msamples/sec |
0.96
|
| Food | 1.84 |
1.76
|
Msamples/sec |
0.96
|
| Danish Mood | 2.29 |
1.88
|
Msamples/sec |
0.82
|
| Procedural Leaves | 1.10 |
1.04
|
Msamples/sec |
0.94
|
| MFEM |
|
|||
| Dynamic AMR | 227.39 |
259.18
|
sec |
0.88
|
| NAMD |
|
|||
| apoa1 | 45.38 |
54.65
|
ms/step |
0.83
|
| f1atpase | 130.50 |
164.51
|
ms/step |
0.79
|
| stmv | 448.57 |
532.74
|
ms/step |
0.84
|
| Octave |
|
|||
| obench | 1.20 |
1.01
|
sec/operation |
1.19
|
| benchmark2 | 0.11 |
0.10
|
sec/operation |
1.13
|
| ONNX Inference |
|
|||
| CPU ResNet50-FP32-batch8 Latency | 63.72 |
69.50
|
ms |
0.92
|
| CPU ResNet50-FP32-batch8 Throughput | 18.33 |
14.24
|
inferences/sec |
0.78
|
| CPU ResNet50-INT8-batch8 Latency | 22.37 |
22.04
|
ms |
1.01
|
| CPU ResNet50-INT8-batch8 Throughput | 46.62 |
47.84
|
inferences/sec |
1.03
|
| CPU SuperResolution-FP32-batch8 Latency | 58.42 |
59.81
|
ms |
0.98
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.87 |
18.75
|
inferences/sec |
0.90
|
| CPU SuperResolution-INT8-batch8 Latency | 21.34 |
23.34
|
ms |
0.91
|
| CPU SuperResolution-INT8-batch8 Throughput | 55.92 |
51.67
|
inferences/sec |
0.92
|
| OpenFOAM |
|
|||
| XiFoam Solver | 803.27 |
183.78
|
sec |
4.37
|
| Options Pricing |
|
|||
| Monte Carlo | 35137.48 |
36451.07
|
options/sec |
1.04
|
| Black-Scholes | 3389.63 |
3316.23
|
Moptions/sec |
0.98
|
| Binomial | 79377.62 |
61793.50
|
options/sec |
0.78
|
| Poisson |
|
|||
| Jacobi Rectangular Grid | 16.05 |
18.11
|
iterations/sec |
1.13
|
| Jacobi Square Grid | 6.19 |
7.08
|
iterations/sec |
1.14
|
| Python 3 |
|
|||
| NumPy Create Matrix | 0.36 |
0.33
|
sec |
1.09
|
| NumPy Add Matrix | 4.44 |
4.77
|
sec |
0.93
|
| NumPy Multiply Matrix | 8.06 |
10.47
|
sec |
0.77
|
| NumPy Invert Matrix | 15.53 |
20.22
|
sec |
0.77
|
| NumPy Sin Matrix | 2.67 |
2.80
|
sec |
0.95
|
| Multi-Matrix | 65.50 |
76.14
|
sec |
0.86
|
| Rodinia CFD |
|
|||
| Pre-Euler | 138.14 |
143.10
|
iterations/sec |
1.04
|
| Rodinia Life Sciences |
|
|||
| Heart Wall | 0.69 |
0.67
|
fps |
0.96
|
| HotSpot | 8.55 |
16.45
|
sec |
0.52
|
| LavaMD | 0.07 |
0.07
|
iterations/sec |
1.00
|
| SRAD | 47.04 |
46.92
|
iterations/sec |
1.00
|
| SRMP |
|
|||
| 2D | 19.45 |
25.14
|
sec |
0.77
|
4.71
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| Viewport Graphics |
|
|||
| 3dsmax | 15.96 |
76.64
|
fps |
4.80
|
| catia | 17.57 |
62.09
|
fps |
3.53
|
| creo | 48.42 |
134.54
|
fps |
2.78
|
| energy | 11.48 |
73.91
|
fps |
6.44
|
| maya | 62.09 |
249.49
|
fps |
4.02
|
| medical | 9.63 |
84.68
|
fps |
8.79
|
| solidworks | 42.90 |
206.70
|
fps |
4.82
|
0.91
| Workload | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|
| WPCstorage |
|
|||
| 3dsmax | 3299.42 |
3496.77
|
points |
1.06
|
| 7zip | 431.06 |
498.45
|
points |
1.16
|
| ccx | 1398.45 |
1654.05
|
points |
1.18
|
| cfd | 1921.51 |
1375.70
|
points |
0.72
|
| energy | 1547.93 |
1119.54
|
points |
0.72
|
| handbrake | 1897.99 |
2018.47
|
points |
1.06
|
| icePack | 1543.34 |
1295.89
|
points |
0.84
|
| maya | 2037.06 |
1753.70
|
points |
0.86
|
| MayaVenice | 472.63 |
385.81
|
points |
0.82
|
| MandE | 1625.72 |
1388.44
|
points |
0.85
|
| mcad | 2612.50 |
3250.83
|
points |
1.24
|
| mozillaVS | 7708.43 |
6412.59
|
points |
0.83
|
| namd | 1250.61 |
1182.26
|
points |
0.94
|
| proddev | 659.82 |
452.78
|
points |
0.69
|
Workload Scores
| Workload | Time Stamp | Execution Time | Reference Result | Measured Result | Unit | SPEC Ratio |
|---|---|---|---|---|---|---|
| 7-Zip | Nov 21, 2024, 10:51:42 AM PST |
2.35
|
||||
| Decompression | 17.48 sec | 16.04 |
17.48
|
sec |
0.92
|
|
| Compression | 72.31 sec | 254.57 |
72.31
|
sec |
3.52
|
|
| Autodesk Inventor | Nov 21, 2024, 10:53:17 AM PST |
0.94
|
||||
| Open Document | 4.88 sec | 4253.73 |
4646.00
|
ms |
0.92
|
|
| Create/Update Files | 7.16 sec | 4973.68 |
5313.00
|
ms |
0.94
|
|
| Rebuild | 10.90 sec | 10590.28 |
10657.00
|
ms |
0.99
|
|
| Render Style/Material | 0.92 sec | 628.78 |
673.00
|
ms |
0.93
|
|
| Blender | Nov 21, 2024, 10:54:25 AM PST |
1.15
|
||||
| Classroom | 109.19 sec | 281.72 |
109.19
|
sec |
2.58
|
|
| BMW27 | 50.19 sec | 43.82 |
50.19
|
sec |
0.87
|
|
| BMW1M | 19.00 sec | 17.74 |
19.00
|
sec |
0.93
|
|
| Island | 36.00 sec | 29.68 |
36.00
|
sec |
0.82
|
|
| Convolution | Nov 21, 2024, 10:58:03 AM PST |
0.85
|
||||
| 20K/100 | 41.43 sec | 0.09 |
0.08
|
iterations/sec |
0.85
|
|
| Data Science | Nov 21, 2024, 10:58:45 AM PST |
1.09
|
||||
| Pandas | 232.94 sec | 131.99 |
126.57
|
sec |
1.04
|
|
| Scikit-learn | 506.48 sec | 449.17 |
501.60
|
sec |
0.90
|
|
| XGBoost | 87.99 sec | 91.50 |
65.32
|
sec |
1.40
|
|
| HandBrake | Nov 21, 2024, 11:12:49 AM PST |
1.05
|
||||
| SVT-AV1 8K to 4K | 242.55 sec | 195.16 |
242.55
|
sec |
0.81
|
|
| x265 4K to 1080p | 52.98 sec | 38.36 |
50.20
|
sec |
0.76
|
|
| x265 4K to 4K | 177.16 sec | 107.73 |
174.91
|
sec |
0.62
|
|
| x264 1080p to 1080p | 21.75 sec | 49.98 |
21.75
|
sec |
2.30
|
|
| GPU H.265 4K to 4K | 75.23 sec | 169.65 |
111.42
|
fps |
0.66
|
|
| GPU H.265 4K to 4K | 65.68 sec | 169.65 |
155.24
|
fps |
0.92
|
|
| GPU H.265 4K to 1080p | 237.37 sec | 128.84 |
200.35
|
fps |
1.55
|
|
| GPU H.265 4K to 1080p | 236.45 sec | 128.84 |
216.95
|
fps |
1.68
|
|
| Hidden Line Removal | Nov 21, 2024, 11:31:26 AM PST |
0.92
|
||||
| Palatov | 17.92 sec | 24.29 |
22.36
|
fps |
0.92
|
|
| Palatov | 18.28 sec | 24.29 |
18.45
|
fps |
0.76
|
|
| LAMMPS | Nov 21, 2024, 11:32:04 AM PST |
1.02
|
||||
| LJ | 19.36 sec | 705.82 |
782.36
|
tau/day |
1.11
|
|
| CHAIN | 17.58 sec | 1190.35 |
1342.27
|
tau/day |
1.13
|
|
| EAM | 21.10 sec | 0.63 |
0.66
|
ns/day |
1.04
|
|
| CHUTE | 11.15 sec | 38.25 |
36.19
|
tau/day |
0.95
|
|
| RHODO | 10.69 sec | 0.26 |
0.24
|
ns/day |
0.92
|
|
| LLVM Clang | Nov 21, 2024, 11:33:25 AM PST |
0.79
|
||||
| PyTorch | 737.87 sec | 562.76 |
714.83
|
sec |
0.79
|
|
| LuxCoreRender | Nov 21, 2024, 11:46:50 AM PST |
0.92
|
||||
| DLSC | 20.87 sec | 2.46 |
2.36
|
Msamples/sec |
0.96
|
|
| Food | 30.50 sec | 1.84 |
1.76
|
Msamples/sec |
0.96
|
|
| Danish Mood | 79.41 sec | 2.29 |
1.88
|
Msamples/sec |
0.82
|
|
| Procedural Leaves | 52.02 sec | 1.10 |
1.04
|
Msamples/sec |
0.94
|
|
| MFEM | Nov 21, 2024, 11:49:53 AM PST |
0.88
|
||||
| Dynamic AMR | 259.18 sec | 227.39 |
259.18
|
sec |
0.88
|
|
| NAMD | Nov 21, 2024, 11:54:13 AM PST |
0.82
|
||||
| apoa1 | 13.43 sec | 45.38 |
54.65
|
ms/step |
0.83
|
|
| f1atpase | 20.74 sec | 130.50 |
164.51
|
ms/step |
0.79
|
|
| stmv | 43.63 sec | 448.57 |
532.74
|
ms/step |
0.84
|
|
| Octave | Nov 21, 2024, 11:55:32 AM PST |
1.16
|
||||
| obench | 37.36 sec | 1.20 |
1.01
|
sec/operation |
1.19
|
|
| benchmark2 | 11.41 sec | 0.11 |
0.10
|
sec/operation |
1.13
|
|
| ONNX Inference | Nov 21, 2024, 11:56:32 AM PST |
1.95
|
||||
| CPU ResNet50-FP32-batch8 Latency | 20.34 sec | 63.72 |
69.50
|
ms |
0.92
|
|
| CPU ResNet50-FP32-batch8 Throughput | 21.20 sec | 18.33 |
14.24
|
inferences/sec |
0.78
|
|
| CPU ResNet50-FP32-batch8 Throughput | 21.73 sec | 18.33 |
13.03
|
inferences/sec |
0.71
|
|
| CPU ResNet50-INT8-batch8 Latency | 20.16 sec | 22.37 |
22.04
|
ms |
1.01
|
|
| CPU ResNet50-INT8-batch8 Throughput | 20.44 sec | 46.62 |
47.84
|
inferences/sec |
1.03
|
|
| CPU ResNet50-INT8-batch8 Throughput | 20.54 sec | 46.62 |
44.87
|
inferences/sec |
0.96
|
|
| CPU SuperResolution-FP32-batch8 Latency | 20.19 sec | 58.42 |
59.81
|
ms |
0.98
|
|
| CPU SuperResolution-FP32-batch8 Throughput | 20.81 sec | 20.87 |
18.75
|
inferences/sec |
0.90
|
|
| CPU SuperResolution-FP32-batch8 Throughput | 21.24 sec | 20.87 |
17.66
|
inferences/sec |
0.85
|
|
| CPU SuperResolution-INT8-batch8 Latency | 20.12 sec | 21.34 |
23.34
|
ms |
0.91
|
|
| CPU SuperResolution-INT8-batch8 Throughput | 20.36 sec | 55.92 |
51.67
|
inferences/sec |
0.92
|
|
| CPU SuperResolution-INT8-batch8 Throughput | 20.45 sec | 55.92 |
43.73
|
inferences/sec |
0.78
|
|
| GPU ResNet50-FP32-batch32 Throughput | 22.62 sec | 3.92 |
18.43
|
inferences/sec |
4.70
|
|
| GPU ResNet50-FP32-batch32 Throughput | 21.35 sec | 3.92 |
18.52
|
inferences/sec |
4.72
|
|
| GPU ResNet50-INT8-batch32 Throughput | 20.86 sec | 1.92 |
40.51
|
inferences/sec |
21.10
|
|
| GPU ResNet50-INT8-batch32 Throughput | 20.84 sec | 1.92 |
40.46
|
inferences/sec |
21.10
|
|
| GPU SuperResolution-FP32-batch32 Throughput | 21.08 sec | 6.59 |
24.82
|
inferences/sec |
3.77
|
|
| GPU SuperResolution-FP32-batch32 Throughput | 21.05 sec | 6.59 |
24.83
|
inferences/sec |
3.77
|
|
| GPU SuperResolution-INT8-batch32 Throughput | 21.00 sec | 1.92 |
27.73
|
inferences/sec |
14.40
|
|
| GPU SuperResolution-INT8-batch32 Throughput | 21.07 sec | 1.92 |
27.79
|
inferences/sec |
14.50
|
|
| OpenFOAM | Nov 21, 2024, 12:03:32 PM PST |
4.37
|
||||
| XiFoam Solver | 198.61 sec | 803.27 |
183.78
|
sec |
4.37
|
|
| XiFoam Solver | 240.26 sec | 803.27 |
227.41
|
sec |
3.53
|
|
| Options Pricing | Nov 21, 2024, 12:10:55 PM PST |
0.93
|
||||
| Monte Carlo | 28.86 sec | 35137.48 |
36451.07
|
options/sec |
1.04
|
|
| Black-Scholes | 21.32 sec | 3389.63 |
3316.23
|
Moptions/sec |
0.98
|
|
| Binomial | 17.05 sec | 79377.62 |
61793.50
|
options/sec |
0.78
|
|
| Poisson | Nov 21, 2024, 12:12:03 PM PST |
1.13
|
||||
| Jacobi Rectangular Grid | 10.06 sec | 16.05 |
17.65
|
iterations/sec |
1.10
|
|
| Jacobi Rectangular Grid | 10.08 sec | 16.05 |
18.11
|
iterations/sec |
1.13
|
|
| Jacobi Square Grid | 10.19 sec | 6.19 |
6.89
|
iterations/sec |
1.11
|
|
| Jacobi Square Grid | 10.21 sec | 6.19 |
7.08
|
iterations/sec |
1.14
|
|
| Python 3 | Nov 21, 2024, 12:12:44 PM PST |
0.88
|
||||
| NumPy Create Matrix | 16.07 sec | 0.36 |
0.33
|
sec |
1.09
|
|
| NumPy Add Matrix | 5.78 sec | 4.44 |
4.77
|
sec |
0.93
|
|
| NumPy Multiply Matrix | 11.50 sec | 8.06 |
10.47
|
sec |
0.77
|
|
| NumPy Invert Matrix | 21.26 sec | 15.53 |
20.22
|
sec |
0.77
|
|
| NumPy Sin Matrix | 3.83 sec | 2.67 |
2.80
|
sec |
0.95
|
|
| Multi-Matrix | 77.36 sec | 65.50 |
76.14
|
sec |
0.86
|
|
| Rodinia CFD | Nov 21, 2024, 12:15:15 PM PST |
1.04
|
||||
| Pre-Euler | 33.07 sec | 138.14 |
143.10
|
iterations/sec |
1.04
|
|
| Rodinia Life Sciences | Nov 21, 2024, 12:15:49 PM PST |
0.84
|
||||
| Heart Wall | 10.71 sec | 0.69 |
0.67
|
fps |
0.96
|
|
| HotSpot | 17.67 sec | 8.55 |
16.45
|
sec |
0.52
|
|
| LavaMD | 14.76 sec | 0.07 |
0.07
|
iterations/sec |
1.00
|
|
| SRAD | 10.27 sec | 47.04 |
46.92
|
iterations/sec |
1.00
|
|
| SRMP | Nov 21, 2024, 12:16:43 PM PST |
0.77
|
||||
| 2D | 25.48 sec | 19.45 |
25.14
|
sec |
0.77
|
|
| Viewport Graphics | Nov 21, 2024, 12:17:10 PM PST |
4.71
|
||||
| 3dsmax | 166.14 sec | 15.96 |
76.64
|
fps |
4.80
|
|
| catia | 195.69 sec | 17.57 |
62.09
|
fps |
3.53
|
|
| creo | 228.51 sec | 48.42 |
134.54
|
fps |
2.78
|
|
| energy | 87.80 sec | 11.48 |
73.91
|
fps |
6.44
|
|
| maya | 112.89 sec | 62.09 |
249.49
|
fps |
4.02
|
|
| medical | 79.15 sec | 9.63 |
84.68
|
fps |
8.79
|
|
| solidworks | 83.89 sec | 42.90 |
206.70
|
fps |
4.82
|
|
| WPCstorage | Nov 21, 2024, 12:34:09 PM PST |
0.91
|
||||
| 3dsmax | 60.18 sec | 3299.42 |
3496.77
|
points |
1.06
|
|
| 7zip | 64.88 sec | 431.06 |
498.45
|
points |
1.16
|
|
| ccx | 13.02 sec | 1398.45 |
1654.05
|
points |
1.18
|
|
| cfd | 13.96 sec | 1921.51 |
1375.70
|
points |
0.72
|
|
| energy | 25.93 sec | 1547.93 |
1119.54
|
points |
0.72
|
|
| handbrake | 18.11 sec | 1897.99 |
2018.47
|
points |
1.06
|
|
| icePack | 67.02 sec | 1543.34 |
1295.89
|
points |
0.84
|
|
| maya | 65.03 sec | 2037.06 |
1753.70
|
points |
0.86
|
|
| MayaVenice | 38.89 sec | 472.63 |
385.81
|
points |
0.82
|
|
| MandE | 24.43 sec | 1625.72 |
1388.44
|
points |
0.85
|
|
| mcad | 65.17 sec | 2612.50 |
3250.83
|
points |
1.24
|
|
| mozillaVS | 33.72 sec | 7708.43 |
6412.59
|
points |
0.83
|
|
| namd | 19.20 sec | 1250.61 |
1182.26
|
points |
0.94
|
|
| proddev | 21.36 sec | 659.82 |
452.78
|
points |
0.69
|
System Configuration Details
MOTHERBOARD
Name: 8C95Model: HP ZBook Power 16 inch G11 A Mobile Workstation PC
Version: KBC Version 08.4B.00
Manufacturer: HP
Serial Number: PTYDB028JJH00Y
BIOS: HP W85 Ver. 01.04.00
BIOS Version: HPQOEM - 1 (2024-08-20)
PROCESSOR
CPU #1: AMD Ryzen 9 PRO 8945HS w/ Radeon 780M Graphics (4001MHz / 8C / 16T)
MEMORY
ChannelA0 (Bottom-Slot 1(left)): Samsung M425R4GA3PB0-CWMOL (32.00 GB / 5600 MHz / DDR5)ChannelB0 (Bottom-Slot 2(right)): Samsung M425R4GA3PB0-CWMOL (32.00 GB / 5600 MHz / DDR5)
Total Memory: 64.00 GB
STORAGE
Disk #1: SAMSUNG MZVL22T0HBLB-00BH1 (1907.73 GB - SCSI)Partition 1: GPT: System (0.25 GB)
Partition 2: GPT: Basic Data (1874.58 GB)
Partition 3: GPT: Unknown (0.87 GB)
Partition 4: GPT: Basic Data (1.00 GB)
Partition 5: GPT: Basic Data (31.00 GB)
Available Volumes
C: (Windows): NTFS (1744.08 GB of 1874.58 GB Available)
NETWORK
Adapter #1: Realtek PCIe GbE Family ControllerType: Ethernet 802.3 | MAC: 30:13:8B:89:D1:53 | Speed: 1000.00 Mbit
Adapter #2: MediaTek Wi-Fi 6E MT7922 (RZ616) 160MHz PCIe Adapter
Type: Ethernet 802.3 | MAC: 8C:53:E6:DB:09:BF | Speed: Not Connected
Adapter #3: Bluetooth Device (Personal Area Network)
Type: Ethernet 802.3 | MAC: 8C:53:E6:DB:09:C0 | Speed: Not Connected
GRAPHICS
Adapter #1: NVIDIA RTX 3000 Ada Generation Laptop GPUVideo Memory: 8.00 GB
Current Resolution: Unknown
Driver Version: 32.0.15.5612 (2024-06-24)
Adapter #2: AMD Radeon(TM) Graphics
Video Memory: 32.80 GB
Current Resolution: 1920x1200 @ 60 Hz (32-bit Color)
Driver Version: 31.0.22052.12001 (2024-06-23)
DISPLAY
Display #1: IVO Internal Display 16.3" (1920x1200)Model: 3E94 | S/N: 4 | Connector: Internal Display (Digital)
Windows Screens
Screen 1: 1920x1200 @ 32 bpp
BATTERY
Battery #1 : P/N: Primary | Mfg: Unknown | Charge Level: 90%
OPERATING SYSTEM
Name: Microsoft Windows 11 Pro 64-bitVersion: 10.0.22631.4460 (Release 2009)
Installation Date: 2024-10-28
Free Memory: 54.44 GB (Physical) | 55.38 GB (Virtual) | 3.88 GB (Paging)
Screensaver: Disabled
Visual Effects Setting: Let Windows Choose
Virtualization Based Security (VBS): Running
Active Power Plan: HP Optimized (Modern Standby (fb5220ff-7e1a-47aa-9a42-50ffbf45c673)