Thick-Restart Lanczos Method for Symmetric Eigenvalue Problems
نویسندگان
چکیده
For real symmetric eigenvalue problems, there are a number of algorithms that are mathematically equivalent, for example, the Lanczos algorithm, the Arnoldi method and the unpreconditioned Davidson method. The Lanczos algorithm is often preferred because it uses signiicantly fewer arithmetic operations per iteration. To limit the maximum memory usage, these algorithms are often restarted. In recent years, a number of eeective restarting schemes have been developed for the Arnoldi method and the Davidson method. This paper describes a simple restarting scheme for the Lanczos algorithm. This restarted Lanczos algorithm uses as many arithmetic operations as the original algorithm. Theoretically, this restarted Lanczos method is equivalent to the implicitly restarted Arnoldi method and the thick-restart Davidson method. Because it uses less arithmetic operations than the others, it is an attractive alternative for solving symmetric eigenvalue problems.
منابع مشابه
TRPL+K: Thick-Restart Preconditioned Lanczos+K Method for Large Symmetric Eigenvalue Problems
The Lanczos method is one of the standard approaches for computing a few eigenpairs of a large, sparse, symmetric matrix. It is typically used with restarting to avoid unbounded growth of memory and computational requirements. Thick-restart Lanczos is a popular restarted variant because of its simplicity and numerically robustness. However, convergence can be slow for highly clustered eigenvalu...
متن کاملExpansion of random field gradients using hierarchical matrices
We present two expansions for the gradient of a random field. In the first approach, we differentiate its truncated KarhunenLoève expansion. In the second approach, the Karhunen-Loève expansion of the random field gradient is computed directly. Both strategies require the solution of dense, symmetric matrix eigenvalue problems which can be handled efficiently by combining hierachical matrix tec...
متن کاملA Communication-Avoiding Thick-Restart Lanczos Method on a Distributed-Memory System
The Thick-Restart Lanczos (TRLan) method is an effective method for solving large-scale Hermitian eigenvalue problems. On a modern computer, communication can dominate the solution time of TRLan. To enhance the performance of TRLan, we develop CA-TRLan that integrates communication-avoiding techniques into TRLan. To study the numerical stability and solution time of CA-TRLan, we conduct numeric...
متن کاملThe Lanczos Method with Semi-inner Product
The spectral transformation Lanczos method is very popular for solving large scale Her-mitian generalized eigenvalue problems. The method uses a special inner product so that the symmetric Lanczos method can be used. Sometimes, a semi-inner product must be used. This may lead to instabilities and breakdown. In this paper, we suggest a cure for breakdown by use of an implicit restart in the Lanc...
متن کاملA Thick-Restart Lanczos Algorithm with Polynomial Filtering for Hermitian Eigenvalue Problems
Polynomial filtering can provide a highly effective means of computing all eigenvalues of a real symmetric (or complex Hermitian) matrix that are located in a given interval, anywhere in the spectrum. This paper describes a technique for tackling this problem by combining a ThickRestart version of the Lanczos algorithm with deflation (‘locking’) and a new type of polynomial filters obtained fro...
متن کامل