On the storage requirement in the out-of-core multifrontal method for sparse factorization
ACM Transactions on Mathematical Software (TOMS)
Efficient Methods for Out-of-Core Sparse Cholesky Factorization
SIAM Journal on Scientific Computing
The Multifrontal Solution of Indefinite Sparse Symmetric Linear
ACM Transactions on Mathematical Software (TOMS)
An Unsymmetrized Multifrontal LU Factorization
SIAM Journal on Matrix Analysis and Applications
The design and implementation of a new out-of-core sparse cholesky factorization method
ACM Transactions on Mathematical Software (TOMS)
Constructing memory-minimizing schedules for multifrontal methods
ACM Transactions on Mathematical Software (TOMS)
Hybrid scheduling for the parallel solution of linear systems
Parallel Computing - Parallel matrix algorithms and applications (PMAA'04)
Reducing the I/O volume in an out-of-core sparse multifrontal solver
HiPC'07 Proceedings of the 14th international conference on High performance computing
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Sparse direct solvers, and in particular multifrontal methods, are widely used in various simulation problems. Because of their large memory requirements, the use of out-of-core solvers is compulsory for large-scale problems, where disks are used to extend the core memory. This study is at the junction of two previous independent works: it extends the problem of the minimization of the volume of I/O [4] in the multifrontal method to the more general flexible parent allocation algorithm [8]. We explain how to compute the I/O volume with respect to this scheme and propose an efficient greedy heuristic which significantly reduces the I/O volume on real-life problems in this new context.