This paper presents a new fine-grained parallel algorithm for computing an incomplete LU
factorization. All nonzeros in the incomplete factors can be computed in parallel and …

With the ubiquity of multicore processors, it is crucial that solvers adapt to the hierarchical
structure of modern architectures. We present ShyLU, a “hybrid-hybrid” solver for general …

Solving sparse triangular systems of linear equations is a performance bottleneck in many
methods for solving more general sparse systems. Both for direct methods and for many …

为解决软件化雷达系统实时处理大规模数据的问题, 提出了一种分层级的分布式并行计算方法,
并设计了一种低延时大规模数据处理能力的软件化雷达系统. 该系统采用三层并行计算方法 …

A novel algorithm for computing the incomplete-LU and Cholesky factorization with 0 fill-in
on a graphics processing unit (GPU) is proposed. It implements the incomplete factorization …

In the present work we present INMOST, the programming platform for mathematical
modelling and its application to a couple of practical problems. INMOST consists of a …

We present specialized implementations of the preconditioned iterative linear system solver
in ILUPACK for Non-Uniform Memory Access (NUMA) platforms and many-core hardware co …

Energy costs nowadays represent a significant share of the total costs of ownership of High
Performance Computing (HPC) systems. In this paper we provide an overview on different …

In this paper we investigate the parallelization of the ILUPACK library for the solution of
sparse linear systems on distributed-memory multiprocessors. The parallelization approach …

We investigate the benefits that an energy-aware implementation of the runtime in charge of
the concurrent execution of ILUPACK—a sophisticated preconditioned iterative solver for …