Hello,
Read this:
About Extreme Scaling in CAE Applications..
I have just read the following about Ansys company:
https://en.wikipedia.org/wiki/Ansys
Notice that Ansys develops and markets finite element analysis software
used to simulate engineering problems.
I think that i have thought about this, and i have "invented"
a Scalable Parallel C++ Conjugate Gradient Linear System Solver Library,
in fact it scales "very" well, my library contains a Scalable Parallel
implementation of Conjugate Gradient Dense Linear System Solver library
that is NUMA-aware and cache-aware, and it contains also a Scalable
Parallel implementation of Conjugate Gradient Sparse Linear
System Solver library that is cache-aware.
Sparse linear system solvers are ubiquitous in high performance
computing (HPC) and often are the most computational intensive parts in
scientific computing codes. A few of the many applications relying on
sparse linear solvers include fusion energy simulation, space weather
simulation, climate modeling, and environmental modeling, and finite
element method, and large-scale reservoir simulations to enhance oil
recovery by the oil and gas industry.
Conjugate Gradient is known to converge to the exact solution in n steps
for a matrix of size n, and was historically first seen as a direct
method because of this. However, after a while people figured out that
it works really well if you just stop the iteration much earlier - often
you will get a very good approximation after much fewer than n steps. In
fact, we can analyze how fast Conjugate gradient converges. The end
result is that Conjugate gradient is used as an iterative method for
large linear systems today.
You can download my Scalable Parallel C++ Conjugate Gradient Linear
System Solver Library from here:
https://sites.google.com/site/scalable68/scalable-parallel-c-conjugate-gradient-linear-system-solver-library
Read the following about Extreme Scaling in CAE Applications, this is
why i have invented my Scalable Parallel C++ Conjugate Gradient Linear
System Solver Library that scales very well:
https://www.cray.com/blog/extreme-scaling-in-cae-applications/
Thank you,
Amine Moulay Ramdane.