NVIDIA V100 versus NVIDIA Volta RTX 8000

Systems

Results

Minimal Cube

Simple cube of static fluid particles at rest

Minimal case to estimate raw performance of solver core

Two sizes:

• Small: ~7m fluid particles (size of relatively small production case, slightly smaller than what we usually recommend for four GPU's)
• Big: ~57m fluid particles (size of a bigger production case)

All runs over 1,000 timesteps

Figure 1.

Dambreak

Collapsing water column under gravity in domain (indicated by lines)

Good case to evaluate performance for tricky particle distributions and indicate whether the load balancing works

Two sizes:

• Small: ~7m fluid particles and ~9m total (slightly smaller than what is recommended for four GPU's)
• Big: ~54m fluid particles and ~64m total (size of bigger production case)

All runs cover 10,000 timesteps

Figure 2.

Altair E-Gearbox

Showcase by Altair for E-Mobility application

Size: ~6.5m fluid particles and ~12m total (slightly smaller than what is recommended for four GPU's)

Run covers 10,000 timesteps

Figure 3.

Aerospace Gearbox

Another showcase for aerospace gearbox applications

Chosen to have another slightly bigger case to fully benefit from four or more GPU's

Size: ~21m fluid particles and ~26.7m total

Run covers 10,000 timesteps

Figure 4.

Conclusions

Results on RTX are generally comparable to DGX-1 with same number of used GPU's. Theoretical performance of the solver core is approximately 10 percent slower on RTX based on Figure 1. This performance difference does not appear in production cases. Generally, performance differences up to 10 percent are not critical as they are not usually noticeable and often depend on minor differences. It is difficult to trace a specific cause because operations and features of the code have different performance characteristics.

Additional Notes