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I have just started using the mkl implemenation of PARDISO. I have never ran into problems before using the stand alone library versions 3 and 4 but I require use of PARDISO on a cluster of workstations and therefore the liscencing method implemented on the stand alone library is not phesible with multiple hosts.
Having edited my code for the mkl implementation the following error arises during phase 11:
*** Error in PARDISO ( reordering_phase) error_num= -180
*** error PARDISO: reordering, symb. factorization
The error flag is then internally set to -3 which simply means 'reordering problem'.
Could someone please shed some light on error code -180.
Regards,
Seb
mkl version: 10.2
fortran compiler: intel-fc-10.1.018-x86_64
Having edited my code for the mkl implementation the following error arises during phase 11:
*** Error in PARDISO ( reordering_phase) error_num= -180
*** error PARDISO: reordering, symb. factorization
The error flag is then internally set to -3 which simply means 'reordering problem'.
Could someone please shed some light on error code -180.
Regards,
Seb
mkl version: 10.2
fortran compiler: intel-fc-10.1.018-x86_64
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Quoting - sebpinski
I have just started using the mkl implemenation of PARDISO. I have never ran into problems before using the stand alone library versions 3 and 4 but I require use of PARDISO on a cluster of workstations and therefore the liscencing method implemented on the stand alone library is not phesible with multiple hosts.
Having edited my code for the mkl implementation the following error arises during phase 11:
*** Error in PARDISO ( reordering_phase) error_num= -180
*** error PARDISO: reordering, symb. factorization
The error flag is then internally set to -3 which simply means 'reordering problem'.
Could someone please shed some light on error code -180.
Regards,
Seb
mkl version: 10.2
fortran compiler: intel-fc-10.1.018-x86_64
Having edited my code for the mkl implementation the following error arises during phase 11:
*** Error in PARDISO ( reordering_phase) error_num= -180
*** error PARDISO: reordering, symb. factorization
The error flag is then internally set to -3 which simply means 'reordering problem'.
Could someone please shed some light on error code -180.
Regards,
Seb
mkl version: 10.2
fortran compiler: intel-fc-10.1.018-x86_64
Hi Seb,
Seems to be some problems in symbolic factorization. Could you provide a part of your code with PARDISO calling to deeper understanding problem?
With best regards,
Alexander Kalinkin
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Quoting - sebpinski
I have just started using the mkl implemenation of PARDISO. I have never ran into problems before using the stand alone library versions 3 and 4 but I require use of PARDISO on a cluster of workstations and therefore the liscencing method implemented on the stand alone library is not phesible with multiple hosts.
Having edited my code for the mkl implementation the following error arises during phase 11:
*** Error in PARDISO ( reordering_phase) error_num= -180
*** error PARDISO: reordering, symb. factorization
The error flag is then internally set to -3 which simply means 'reordering problem'.
Could someone please shed some light on error code -180.
Regards,
Seb
mkl version: 10.2
fortran compiler: intel-fc-10.1.018-x86_64
Having edited my code for the mkl implementation the following error arises during phase 11:
*** Error in PARDISO ( reordering_phase) error_num= -180
*** error PARDISO: reordering, symb. factorization
The error flag is then internally set to -3 which simply means 'reordering problem'.
Could someone please shed some light on error code -180.
Regards,
Seb
mkl version: 10.2
fortran compiler: intel-fc-10.1.018-x86_64
seb,
is this windows or linux? and what is this architecrture, 32 or 64 bit?
--Gennady
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I'm using linux 64-bit.
The problem is now solved. It turns out that it was my library linking that was the problem even though there were no compiler errors.
I was linking to system installed -pthread when I should have been linking to the mkl's own -lpthread.
Thanks for the help anyway, still not sure what the error code means but hey, it works.
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