84 citations · 222 across the 12 of their papers we have counts for
14 papers
Optimizing Shift Selection in Multilevel Monte Carlo for Disconnected Diagrams in Lattice QCD
Travis Whyte, Andreas Stathopoulos, Eloy Romero +1
The calculation of disconnected diagram contributions to physical signals is a computationally expensive task in Lattice QCD. To extract the physical signal, the trace of the inver…
Probing for the Trace Estimation of a Permuted Matrix Inverse Corresponding to a Lattice Displacement
Heather Switzer, Andreas Stathopoulos, Eloy Romero +2
In this work, we study probing for the more general problem of computing the trace of a permutation of , say . The motivation comes from Lattice QCD where we need…
Multigrid deflation for Lattice QCD
Eloy Romero, Andreas Stathopoulos, Kostas Orginos
Computing the trace of the inverse of large matrices is typically addressed through statistical methods. Deflating out the lowest eigenvectors or singular vectors of the matrix red…
TRPL+K: Thick-Restart Preconditioned Lanczos+K Method for Large Symmetric Eigenvalue Problems
Lingfei Wu, Fei Xue, Andreas Stathopoulos
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 gr…
Algorithms for Disconnected Diagrams in Lattice QCD
Arjun Singh Gambhir, Andreas Stathopoulos, Kostas Orginos +3
Computing disconnected diagrams in Lattice QCD (operator insertion in a quark loop) entails the computationally demanding problem of taking the trace of the all to all quark propag…
PRIMME_SVDS: A High-Performance Preconditioned SVD Solver for Accurate Large-Scale Computations
Lingfei Wu, Eloy Romero, Andreas Stathopoulos
The increasing number of applications requiring the solution of large scale singular value problems have rekindled interest in iterative methods for the SVD. Some promising recent…
Deflation as a Method of Variance Reduction for Estimating the Trace of a Matrix Inverse
Arjun Singh Gambhir, Andreas Stathopoulos, Kostas Orginos
Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC)…
Estimating the Trace of the Matrix Inverse by Interpolating from the Diagonal of an Approximate Inverse
Lingfei Wu, Jesse Laeuchli, Vassilis Kalantzis +2
A number of applications require the computation of the trace of a matrix that is implicitly available through a function. A common example of a function is the inverse of a large,…
Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma
Lingfei Wu, Kesheng Wu, Alex Sim +5
A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important…
A Preconditioned Hybrid SVD Method for Computing Accurately Singular Triplets of Large Matrices
Lingfei Wu, Andreas Stathopoulos
The computation of a few singular triplets of large, sparse matrices is a challenging task, especially when the smallest magnitude singular values are needed in high accuracy. Most…
Extending the eigCG algorithm to nonsymmetric Lanczos for linear systems with multiple right-hand sides
A. M. Abdel-Rehim, Andreas Stathopoulos, Kostas Orginos
The technique that was used to build the EigCG algorithm for sparse symmetric linear systems is extended to the nonsymmetric case using the BiCG algorithm. We show that, similarly…
Hierarchical probing for estimating the trace of the matrix inverse on toroidal lattices
Andreas Stathopoulos, Jesse Laeuchli, Kostas Orginos
The standard approach for computing the trace of the inverse of a very large, sparse matrix is to view the trace as the mean value of matrix quadratures, and use the Monte Carl…
Extending the eigCG algorithm to non-symmetric linear systems with multiple right-hand sides
Abdou Abdel-Rehim, Kostas Orginos, Andreas Stathopoulos
For Hermitian positive definite linear systems and eigenvalue problems, the eigCG algorithm is a memory efficient algorithm that solves the linear system and simultaneously compute…
Computing and deflating eigenvalues while solving multiple right hand side linear systems in Quantum Chromodynamics
Andreas Stathopoulos, Kostas Orginos
We present a new algorithm that computes eigenvalues and eigenvectors of a Hermitian positive definite matrix while solving a linear system of equations with Conjugate Gradient (CG…