Dell PowerEdge C4140 Deep Learning Performance Comparison - Scale-up vs. Scale - Page 45

below show comparable results for PowerEdge C4140-K multi-node

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Deep Learning Performance: Scale-up vs Scale-out converged faster than Inception-v4. On the other hand, the model VGG-19 didn't produce acceptable accuracy suggesting it requires over 90 epochs to converge. Figure 38 below show comparable results for PowerEdge C4140-K (multi-node) - V100 SXM2 Figure 38: Training long tests to extract accuracy convergence and training time with PowerEdge C4140K multi-node and different models Architectures & Technologies Dell EMC | Infrastructure Solutions Group 44

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Deep Learning Performance: Scale-up vs Scale-out
Architectures & Technologies
Dell
EMC
| Infrastructure Solutions Group
44
converged faster than Inception-v4. On the other hand, the model VGG-
19 didn’
t produce
acceptable accuracy suggesting it requires over 90 epochs to converge.
Figure 38
below show comparable results for PowerEdge C4140-K (multi-node)
–
V100 SXM2
Figure 38: Training long tests to extract accuracy convergence and training time with PowerEdge C4140-
K multi-node and different models