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Hi All,
I want to use sparse matrix-dense vector multiplication. Matrix is stored in CSR(compressed sparse row) format.
My matrix is of datatype int and
vector is of datatype double.
I searched for routines and found mkl_dcsrmv, mkl_dcsrgemv but both need to have same data type(double).
Is there any other way so that I can use matrix in int and vector in double and perform sparse matrix-dense vector multiplication using routines..?
Regards,
M.Kiran Kumar.
I want to use sparse matrix-dense vector multiplication. Matrix is stored in CSR(compressed sparse row) format.
My matrix is of datatype int and
vector is of datatype double.
I searched for routines and found mkl_dcsrmv, mkl_dcsrgemv but both need to have same data type(double).
Is there any other way so that I can use matrix in int and vector in double and perform sparse matrix-dense vector multiplication using routines..?
Regards,
M.Kiran Kumar.
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Kiran, you right. No such m-v routines in MKL ( only for single and double precision).
for your case, you can try to explicity convert int -> double
say:
int val;
(double)val;
or
static_cast
--Gennady
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