We need to get all (a part of them won't suffice) the eigenvalues of a very large (≈10^6x10^6) very sparse (≈10^7 non-zero entries) non-hermitiancomplex (but symmetric!) matrix. We have access to computer clusters from with Intel® Gold 6148 Skylake @ 2.4 [GHz] CPUs with up to 752 [GB] of RAM each (shared or distributed memory). The cluster already have an installation of Intel® Math Kernel Library.
MKL : Major version: 2018, Minor version: 0, Update version: 3, Build: 20180406, Platform: Intel(R) 64 architecture, Processor optimization: Intel(R) Advanced Vector Extensions 512 (Intel(R) AVX-512) enabled processors.
OS : CentOS Linux release 7.7.1908 (Core).
Compiler : mpicc (ICC) 18.0.3 20180410
Questions :
- Which package/library/function should I use ? I thought I could use zfeast_hcsrev from FEAST, but from what the documentation says, it seems like it's restricted to hermitian matrices (the h in hcsr stands for hermitian).
- If that function takes parameters apart from the matrix, do they have default values. If they don't, what would you recommend or where could I find information to determine those values myself ?
- Is there an easy way to import my matrix which is in Matrix Market format (.mtx) to pass it to that function ?
- Is there any particular compiler options I should use ?
(I'm a graduate student in physics so computer science isn't my specialty)
Thanks,
Gabriel