6 papers · 1 filter
Factored Sparse Approximate Inverse Preconditioning via Spectral Optimization
Francesco Brarda, Tianshi Xu, Vassilis Kalantzis +2
In this paper, we study value selection for fixed-pattern factorized sparse approximate inverse preconditioners. Given a prescribed sparsity pattern for a factor we choose its…
Hybrid Digital-Analog Approximate Inverse Preconditioning for Krylov Methods
Shikhar Shah, Rui Peng Li, Tayfun Gokmen +3
Analog in-memory computing enables highly parallel matrix-vector multiplications with reduced data movement, but the resulting operations are noisy, quantized, and affected by devi…
Analysis of Power Iteration Algorithm with Partially Observed Matrix-vector Products
Soumyadip Ghosh, Lior Horesh, Vassilis Kalantzis +3
We consider the problem of computing the dominant eigenvector of a symmetric matrix via the power iteration algorithm subject to constraints in the computation of matrix-vector pr…
Regenerative Ulam-von Neumann Algorithm: An Innovative Markov chain Monte Carlo Method for Matrix Inversion
Soumyadip Ghosh, Lior Horesh, Vassilis Kalantzis +2
This paper presents a regenerative variant of the classical Ulam-von Neumann Markov chain Monte Carlo algorithm for the approximation of the matrix inverse. The algorithm presented…
Straggler-tolerant stationary methods for linear systems
Vassilis Kalantzis, Yuanzhe Xi, Lior Horesh +1
In this paper, we consider the iterative solution of linear algebraic equations under the condition that matrix-vector products with the coefficient matrix are computed only partia…
Cucheb: A GPU implementation of the filtered Lanczos procedure
Jared L. Aurentz, Vassilis Kalantzis, Yousef Saad
This paper describes the software package Cucheb, a GPU implementation of the filtered Lanczos procedure for the solution of large sparse symmetric eigenvalue problems. The filtere…