The common trend that has been seen throughout this
study is the versatility of both the RTX 6000 Ada
Generation and A100 GPUs. They oer tremendous
power-per-dollar whether running as a standalone GPU
or in multiples, giving the user some flexibility on HPC
packs required.
In conclusion, leveraging GPUs for HPC tasks has the
potential to displace CPUs as the main workhorse for
such applications. With respect to engineering simulation,
particularly in the Ansys software ecosystem, GPUs can
change a solver paradigm that has existed for decades.
For the same price (or vastly lower), one can acquire
hardware with performance that is several times faster
than the equivalently sized CPU cluster. From budget
system users to full-fledged simulation teams, there is a
GPU solution that can provide simulation results faster and
cheaper in a more compact footprint. This study
showcased the significant capabilities of GPU solving
capabilities within Ansys Fluent, and the results speak
for themselves. While the equivalent CPU cores depend
highly on the model size and type of solver method, the
results are clear: GPU solving is the future and standard
of the simulation industry.
Study Conclusions
Continued...
©2024 Rand Simulation 11
The Impact of GPU Solving on Simulation Performance
