Dear PETSc Users and Developers,
The PETSc/TAO team at Argonne National Laboratory has an opening for a
postdoctoral researcher to work on development of robust and efficient
algebraic solvers and related technologies targeting exascale-class
supercomputers -- such as the Aurora machine slated
Dear PETSc Users and Developers,
The Laboratory for Applied Mathematics, Numerical Software, and Statistics
(LANS, https://www.anl.gov/mcs/lans) in the Mathematics and Computer Science
Division at Argonne National Laboratory -- which has served as the "home" for
PETSc development for over two
Hi Eda,
If you are using the MATLAB k-means function, calling it like
idx = kmeans(X,k)
will give you the index set, but if you do
[idx,C] = kmeans(X,k)
then you will also get a matrix C which contains the cluster centroids. Is this
not what you need?
--Richard
On 5/22/20 10:38 AM, Eda
Yes, Junchao said he gets the segfault, but it works for Karl. Sounds like this
may be a case of one compiler liking the definitions for complex that Thrust
uses, and some not, as Stefano says. Karl and Junchao, can you please share the
version of the compilers (and maybe associated settings)
Hi Eda,
Thanks for your reply. I'm still trying to understand why you say you need to
duplicate the row vectors across all processes. When I have implemented
parallel k-means, I don't duplicate the row vectors. (This would be very
unscalable and largely defeat the point of doing this with MPI
Hi Eda,
I think that you probably want to use VecScatter routines, as Junchao
has suggested, instead of the lower level star forest for this. I
believe that VecScatterCreateToZero() is what you want for the broadcast
problem you describe, in the second part of your question. I'm not sure
what
Hi Xiangdong,
Maybe I am misunderstanding you, but it sounds like you want an exact direct
solution, so I don't understand why you are using an incomplete factorization
solver for this. SuperLU_DIST (as Mark has suggested) or MUMPS are two such
packages that provide MPI-parallel sparse LU
We will let you know when this is ready, Xiangdong.
Let me address a part of your original question that I don't think anyone else
noticed:
In my current code, the Jacobian matrix preallocated and assembled as BAIJ
format. Do I have to rewrite this part of code to preallocate and assemble the
Xiangdong,
cuSPARSE does support block compressed sparse row (BAIJ) format, but we don't
currently support that cuSPARSE functionality in PETSc. It should be easy to
add, but we are currently refactoring the way we interface with third party GPU
libraries such as cuSPARSE, and it would
ta in one process, I got a crash and error saying
> object too big. Thank you for any insight.
>
> 1) Always send the complete error.
>
> 2) It sounds like you got an out of memory error for that process.
>
>Matt
>
> Regards,
>
> Karl
>
> On Thu, Jul 18, 2019 a
Hi Kun and Karl,
If you are using the AIJMKL matrix types and have a recent version of MKL, the
AIJMKL code uses MKL's inspector-executor sparse BLAS routines, which are
described at
https://software.intel.com/en-us/mkl-developer-reference-c-inspector-executor-sparse-blas-routines
The
Hi Ale,
I don't know if this has anything to do with the strange performance you are
seeing, but I notice that some of your Intel MPI settings are inconsistent and
I'm not sure what you are intending. You have specified a value for
I_MPI_PIN_DOMAIN and also a value for
Hi Kun,
I'm the author of most of the AIJMKL stuff in PETSc. My apologies for having
inadvertently omitted these function prototypes for these interfaces; I'm glad
that Satish's patch has fixed this.
I want to point out that -- though I can envision some scenarios in which one
would want to
13 matches
Mail list logo
