我使用python稀疏模块来计算特征值问题。它是一个非常大的稀疏矩阵，最终会产生大量内存需求。但奇怪的是我使用的是具有256GB内存的集群，这对我的问题来说应该是足够的。但是我得到的内存错误不足如下。我想知道是否有人会给我一个如何解决这个问题的提示？
Not enough memory to perform factorization.
Traceback (most recent call last):
File "init_Re620eta1_40X_2Z_omega10.py", line 158, in <module>
exec_stabDiagBatchFFfollow_2D(geometry,baseFlowFolder,baseFlowVarb,baseFlowMethod,h,y_max_factor_EVP,Ny_EVP,Nz_EVP,x_p_stabDiag,x_p_orig,eigSolver,noEigs2solv,noEigs2save,SIGMA0,arnoldiTol,OmegaTol,disc_y,disc_z,y_i_factor_EVP,z_i_factor_EVP,periodicZ,BC_top,customComment,BETA,ALPHA_min,ALPHA_max,noALPHA,ALPHA_start,xp_start,u_0,nu_0,y_cut,ParallelFlowA,comm,rank,RESTART,saveJobStep,saveResultFormat)
File "/lustre/cray/ws8/ws/iagyonwu-Re620eta1/omega10DNS_wTS_icoPerbFoam/LST_functions_linstab2D_Temperal_mpi_multiTracking4.py", line 3893, in exec_stabDiagBatchFFfollow_2D
OMEGA, eigVecs = sp.linalg.eigs(L0, k=noEigs2solv, sigma=SIGMA, v0=options_v0, tol=arnoldiTol)
File "/opt/python/3.6.1.1/lib/python3.6/site-packages/scipy/sparse/linalg/eigen/arpack/arpack.py", line 1288, in eigs
symmetric=False, tol=tol)
File "/opt/python/3.6.1.1/lib/python3.6/site-packages/scipy/sparse/linalg/eigen/arpack/arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "/opt/python/3.6.1.1/lib/python3.6/site-packages/scipy/sparse/linalg/eigen/arpack/arpack.py", line 907, in __init__
self.M_lu = splu(M)
File "/opt/python/3.6.1.1/lib/python3.6/site-packages/scipy/sparse/linalg/dsolve/linsolve.py", line 267, in splu
ilu=False, options=_options)
MemoryError
matirx的典型大小为50000x50000，此后遵循L0的结构：
