On Tue, Apr 23, 2024 at 4:00 PM Yongzhong Li
wrote:
> Thanks Barry! Does this mean that the sparse matrix-vector products, which
> actually constitute the majority of the computations in my GMRES routine in
> PETSc, don’t utilize multithreading? Only basic vector operations such as
> VecAXPY and
Yes, only the routines that can explicitly use BLAS have multi-threading.
PETSc does support using nay MPI linear solvers from a sequential (or
OpenMP) main program using the
https://urldefense.us/v3/__https://petsc.org/release/manualpages/PC/PCMPI/*pcmpi__;Iw!!G_uCfscf7eWS!axQjxZeWC27cy3W
No, I think sparse matrix-vector products (MatMult in petsc) can be
accelerated with multithreading. petsc does not do that, but one can use
other libraries, such as MKL for that.
--Junchao Zhang
On Tue, Apr 23, 2024 at 3:00 PM Yongzhong Li
wrote:
> Thanks Barry! Does this mean that the spars
Thanks Barry! Does this mean that the sparse matrix-vector products, which
actually constitute the majority of the computations in my GMRES routine in
PETSc, don’t utilize multithreading? Only basic vector operations such as
VecAXPY and VecDot or dense matrix operations in PETSc will benefit fro
Intel MKL or OpenBLAS are the best bet, but for vector operations they will
not be significant since the vector operations do not dominate the computations.
> On Apr 23, 2024, at 3:23 PM, Yongzhong Li
> wrote:
>
> Hi Barry,
>
> Thank you for the information provided!
>
> Do you think dif
Hi Barry,
Thank you for the information provided!
Do you think different BLAS implementation will affect the multithreading
performance of some vectors operations in GMERS in PETSc?
I am now using OpenBLAS but didn’t see much improvement when theb
multithreading are enabled, do you think other
The code is behaving as it should, IMHO.
Here is a way to have the Mat stored the same independently of the number of
processes.
[…]
global_rows, global_cols = input_array.T.shape
size = ((None, global_rows), (0 if COMM_WORLD.Get_rank() <
COMM_WORLD.Get_size() - 1 else global_cols, global_cols))
Hello,
The following code returns a different answer depending on how many
processors I use. With one processor, the last MPIAIJ matrix is correctly
formed:
row 0: (0, 1.) (1, 2.) (2, 3.) (3, 4.) (4, -1.)
row 1: (0, 5.) (1, 6.) (2, 7.) (3, 8.) (4, -2.)
row 2: (0, 9.) (1, 10.) (2, 11.)
