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Why is Intel MKL failing to solve this eigenproblem while SciPy has no problems

I am trying to solve a generalized eigenvalue problem (I want both the eigenvalues and eigenvectors):

[A]{x} = lambda[B]{x}

Or equivalent (Finite Element Method):

[M]{x} = (1/w^2)[K]{x}

Where [M]=[A] and [K]=[B] (mass and stiffness matrices, respectively).

In order to impose Dirichlet boundary conditions, [M] is singular in my case.

I have both [M] and [K] in plain text files. These matrices are stored in COO format, 0-based indexing, not sorted.

My files (attached, or download from Google Drive


kc: where K columns are stored
kr: where K rows are stored
kv: where K values are stored
mc, mr, mv: analogous to K, but for the M matrix


Using the data from the files, I can solve the problem with SciPy (Python). Since this is a FEA problem, I've also solved it in Abaqus CAE, so I know for a fact that both eigenvalues and eigenvectors are correctly calculated in SciPy:


MODE    ABAQUS (w^2)    SciPy (w^2)
1       +6.07235E+06    +6.50440E+06
2       +2.28087E+08    +2.44463E+08
3       +1.67357E+09    +1.79572E+09
4       +3.36973E+09    +3.37316E+09
5       +5.88655E+09    +6.32761E+09
(1/lambda = w^2)


My Python code:


from scipy.sparse import coo_matrix
from scipy.sparse.linalg import eigs
from numpy import real

rows = 610
cols = 610
a_nnz = 4628
b_nnz = 9266

# read a
with open('./coo/mr') as f: a_row_indx = [int(i) for i in f]
with open('./coo/mc') as f: a_col_indx = [int(i) for i in f]
with open('./coo/mv') as f: a_val_indx = [float(i) for i in f]

# read b
with open('./coo/kr') as f: b_row_indx = [int(i) for i in f]
with open('./coo/kc') as f: b_col_indx = [int(i) for i in f]
with open('./coo/kv') as f: b_val_indx = [float(i) for i in f]

a = coo_matrix((a_val_indx, (a_row_indx, a_col_indx)), shape=(rows, cols))
b = coo_matrix((b_val_indx, (b_row_indx, b_col_indx)), shape=(rows, cols))

eigenvalues, eigenvectors = eigs(A=a, M=b, k=10)

val = real(eigenvalues) # to remove "+0j", eigenvalues are real
v = 1.0/val


My question is, why is Intel MKL failing to solve this problem? I've tried tinkering with the code, but I always get errors or exceptions:


pm(3) = 1 ! -> Exception thrown at 0x00007FFCE77556EC (mkl_core.dll) in Console1.exe: 0xC0000005: Access violation accessing location 0x0000000000000000.


My Fortran code (Visual Studio):


include 'mkl_solvers_ee'
include 'mkl_spblas'

program main

	use mkl_solvers_ee
	use mkl_spblas
	use, intrinsic :: iso_c_binding , only : c_int, c_double
	implicit none
	type(sparse_matrix_t) :: a
	type(sparse_matrix_t) :: b
	integer(c_int), parameter :: rows = 610
	integer(c_int), parameter :: cols = 610
	integer(c_int), parameter :: a_nnz = 4628
	integer(c_int), parameter :: b_nnz = 9266
	integer(c_int) :: a_row_indx(a_nnz)
	integer(c_int) :: a_col_indx(a_nnz)
	real(c_double) :: a_values(a_nnz)
	integer(c_int) :: b_row_indx(b_nnz)
	integer(c_int) :: b_col_indx(b_nnz)
	real(c_double) :: b_values(b_nnz)
	integer :: stat
	character, parameter :: which = 'S'
	integer(c_int) :: pm(128)
	type(matrix_descr), parameter :: descra = matrix_descr(type = sparse_matrix_type_general, mode = sparse_fill_mode_upper, diag = sparse_diag_non_unit)
	type(matrix_descr), parameter :: descrb = matrix_descr(type = sparse_matrix_type_general, mode = sparse_fill_mode_upper, diag = sparse_diag_non_unit)
	integer(c_int), parameter :: k0 = 10
	integer(c_int) :: k
	real(c_double) :: e(k0), ee(k0)
	real(c_double) :: x(k0, cols)
	real(c_double) :: res(k0)
	type(sparse_matrix_t) :: acsr
	type(sparse_matrix_t) :: bcsr
	integer :: i
	! read a
	open(unit=1, file="./coo/mr")
	open(unit=2, file="./coo/mc")
	open(unit=3, file="./coo/mv")
	do i = 1, a_nnz
		read(1, *) a_row_indx(i)
		read(2, *) a_col_indx(i)
		read(3, *) a_values(i)
	end do
	! read b
	open(unit=1, file="./coo/kr")
	open(unit=2, file="./coo/kc")
	open(unit=3, file="./coo/kv")
	do i = 1, b_nnz
		read(1, *) b_row_indx(i)
		read(2, *) b_col_indx(i)
		read(3, *) b_values(i)
	end do
	a_row_indx(:) = a_row_indx(:) + 1
	a_col_indx(:) = a_col_indx(:) + 1

	b_row_indx(:) = b_row_indx(:) + 1
	b_col_indx(:) = b_col_indx(:) + 1
	stat = mkl_sparse_d_create_coo(a, sparse_index_base_one, rows, cols, a_nnz, a_row_indx, a_col_indx, a_values)
	stat = mkl_sparse_d_create_coo(b, sparse_index_base_one, rows, cols, b_nnz, b_row_indx, b_col_indx, b_values)
	stat = mkl_sparse_convert_csr(a, sparse_operation_non_transpose, acsr)
	stat = mkl_sparse_convert_csr(b, sparse_operation_non_transpose, bcsr)
	stat = mkl_sparse_ee_init(pm)
	!pm(1) = 0
	!pm(2) = 6
	!pm(3) = 2
	!pm(4) = 512
	!pm(5) = 60 ! 10000 
	!pm(6) = 512
	!pm(7) = 0
	!pm(8) = 0
	!pm(9) = 0
	!pm(3) = 1 ! -> Exception thrown at 0x00007FFCE77556EC (mkl_core.dll) in Console1.exe: 0xC0000005: Access violation accessing location 0x0000000000000000.
	stat = mkl_sparse_d_gv(which, pm, acsr, descra, bcsr, descrb, k0, k, e, x, res)
	ee(:) = 1.0 / e(:)
end program main
!	0	SPARSE_STATUS_SUCCESS			The operation was successful.
!	1	SPARSE_STATUS_NOT_INITIALIZED	The routine encountered an empty handle or matrix array.
!	2	SPARSE_STATUS_ALLOC_FAILED		Internal memory allocation failed.
!	3	SPARSE_STATUS_INVALID_VALUE		The input parameters contain an invalid value.
!	5	SPARSE_STATUS_INTERNAL_ERROR	An error in algorithm implementation occurred.
!	6	SPARSE_STATUS_NOT_SUPPORTED		The requested operation is not supported.


I have wasted all day looking at this code and I can't tell what I am doing wrong. Any help is greatly appreciated.


Code correction:

character, parameter :: which = 'L'

Since I want the lowest w^2, i.e, the largest eigenvalues (lambda = 1/w^2).

pm(3) = 1 ! -> Exception thrown at 0x00007FFCE77556EC (mkl_core.dll) in Console1.exe: 0xC0000005: Access violation accessing location 0x0000000000000000.
pm(3) = 2 ! -> Stack trace terminated abnormally. forrtl: severe (157): Message not found - Unhandled exception at 0x00007FF92E64ED79 (ntdll.dll) in Console1.exe: 0xC0000374: A heap has been corrupted (parameters: 0x00007FF92E6B77F0).

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