Grid is a distributed high performance computing paradigm that offers various types of
resources (like computing, storage, communication) to resource-intensive user tasks. These …

Contemporary GPUs have significantly higher arithmetic throughput than a memory
throughput. Hence, many GPU kernels are memory bound and cannot exploit arithmetic …

Dependence between iterations in sparse computations causes inefficient use of memory
and computation resources. This paper proposes sparse fusion, a technique that generates …

This paper proposes a fine-grained implementation of matrix-free Conjugate Gradient (CG)
solver for Finite Element Analysis (FEA) using Graphics Processing Unit (GPU) …

Due to the rapid advance of general-purpose graphics processing unit (GPU), it is an active
research topic to study performance improvement of non-linear optimization with parallel …

This paper proposes a strategy for the efficient implementation of Fixed Grid Finite Element
Analysis (FGFEA) method on Graphics Processing Units (GPUs). Such a strategy makes use …

This work investigates a variant of the conjugate gradient (CG) method and embeds it into
the context of high-order finite-element schemes with fast matrix-free operator evaluation …

Accelerating numerical algorithms for solving sparse linear systems on parallel architectures
has attracted the attention of many researchers due to their applicability to many …

Many problems in geophysical and atmospheric modelling require the fast solution of elliptic
partial differential equations (PDEs) in “flat” three dimensional geometries. In particular, an …

In this work we present a new alternate way to formulate the finite element method (FEM) for
parallel processing based on the solution of single mesh elements called FEM-SES. The key …