Privacy-preserving tensor decomposition over encrypted data in a federated cloud environment
Tensors are popular and versatile tools which model multidimensional data. Tensor
decomposition has emerged as a powerful technique dealing with multidimensional data …
decomposition has emerged as a powerful technique dealing with multidimensional data …
The eigenvalues slicing library (EVSL): Algorithms, implementation, and software
This paper describes a software package called EVSL (for eigenvalues slicing library) for
solving large sparse real symmetric standard and generalized eigenvalue problems. As its …
solving large sparse real symmetric standard and generalized eigenvalue problems. As its …
Efficient shift-and-invert preconditioning for multi-gpu accelerated density functional calculations
To accelerate the iterative diagonalization of electronic structure calculations, we propose a
new inexact shift-and-invert (ISI) preconditioning method. The key idea is to improve shift …
new inexact shift-and-invert (ISI) preconditioning method. The key idea is to improve shift …
Efficient parallel implementations of sparse triangular solves for GPU architectures
The sparse triangular matrix solve (SpTrSV) is an important computation kernel that is
demanded by a variety of numerical methods such as the Gauss-Seidel iterations. However …
demanded by a variety of numerical methods such as the Gauss-Seidel iterations. However …
EigenRec: generalizing PureSVD for effective and efficient top-N recommendations
AN Nikolakopoulos, V Kalantzis, E Gallopoulos… - … and Information Systems, 2019 - Springer
We introduce EigenRec, a versatile and efficient latent factor framework for top-N
recommendations that includes the well-known PureSVD algorithm as a special case …
recommendations that includes the well-known PureSVD algorithm as a special case …
Sublinear time spectral density estimation
We present a new sublinear time algorithm for approximating the spectral density
(eigenvalue distribution) of an n× n normalized graph adjacency or Laplacian matrix. The …
(eigenvalue distribution) of an n× n normalized graph adjacency or Laplacian matrix. The …
Dynamic Precision Approach for Accelerating Large-Scale Eigenvalue Solvers in Electronic Structure Calculations on Graphics Processing Units
Single precision (SP) arithmetic can be greatly accelerated as compared to double precision
(DP) arithmetic on graphics processing units (GPUs). However, the use of SP in the whole …
(DP) arithmetic on graphics processing units (GPUs). However, the use of SP in the whole …
A two-level GPU-accelerated incomplete LU preconditioner for general sparse linear systems
This paper presents a parallel preconditioning approach based on incomplete LU (ILU)
factorizations in the framework of Domain Decomposition (DD) for general sparse linear …
factorizations in the framework of Domain Decomposition (DD) for general sparse linear …
Large eigenvalue problems in coarse-grained dynamic analyses of supramolecular systems
P Koehl - Journal of chemical theory and computation, 2018 - ACS Publications
Computational methods ranging from all-atom molecular dynamics simulations to coarse-
grained normal-mode analyses based on simplified elastic networks provide a general …
grained normal-mode analyses based on simplified elastic networks provide a general …
Stable computation of generalized matrix functions via polynomial interpolation
Generalized matrix functions (GMFs) extend the concept of a matrix function to rectangular
matrices via the singular value decomposition. Several applications involving directed …
matrices via the singular value decomposition. Several applications involving directed …