The Impact of GPU Solving on Simulation Performance
©2024 Rand Simulation 3
Introduction:
Setting The Stage For
GPU Solving
As simulation has become more prevalent in the product
development environment, the computational require-
ments for running ever more complex engineering simula-
tions have increased significantly. To meet that need,
high-performance computing (HPC) has empowered
engineers with hardware capabilities that allow them to
not only study more complex systems, but also collect
results faster than ever before. Running simulations in
parallel on tens, hundreds, or even thousands of CPU
cores can now deliver results in hours rather than days.
In parallel, the GPU industry is becoming the backbone
of complex computations, particularly for AI and now, most
recently, the HPC space. Seeing the capability that GPU
computing oers Ansys has integrated their Native GPU
solver into many of their flagship tools, including Fluent.
Instead of relying on many CPUs to crunch the numbers,
what if a single GPU could provide the equivalent
computing power of hundreds of CPU cores? And what if
GPU computational horsepower was significantly cheaper
than the combined hardware and licensing costs of
CPU-driven solvers? This question provides an exciting
value proposition we will be diving into.
