International audienceOver the past few years, multicore systems have become more and more powerful and, thereby, very useful in high-performance computing. However, many applications, such as some linear algebra algorithms, still cannot take full advantage of these systems. This is mainly due to the shortage of optimization techniques dealing with irregular control structures. In particular, the well-known polyhedral model fails to optimize loop nests whose bounds and/or array references are not affine functions. This is more likely to occur when handling sparse matrices in their packed formats. In this paper, we propose to use 2d-packed layouts and simple affine transformations to enable optimization of triangular and banded matrix operat...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
Combinatorial scientific computing plays an important enabling role in computational science, partic...
Large sparse symmetric matrix problems arise in a number of scientific and engineering fields such a...
Matrix computations are expensive, and GPUs have the potential to deliver results at reduced cost b...
Abstract—This paper presents a data layout optimization technique for sequential and parallel progra...
Almost every modern processor is designed with a memory hierarchy organized into several levels, eac...
42 pages, available as LIP research report RR-2009-15Numerical linear algebra and combinatorial opti...
In a recent paper it was shown how memory traffic can be diminished by reformulating the classic alg...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
This work investigates the problem of permuting a sparse rectangular matrix into block diagonal form...
We focus on two known NP-hard problems that have applications in sparse matrix computations: the env...
Efficient memory usage is crucial for data-intensive applications as a smaller memory footprint ensu...
The present work presents a strategy to increase the arithmetic intensity of the solvers. Namely, we...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
Combinatorial scientific computing plays an important enabling role in computational science, partic...
Large sparse symmetric matrix problems arise in a number of scientific and engineering fields such a...
Matrix computations are expensive, and GPUs have the potential to deliver results at reduced cost b...
Abstract—This paper presents a data layout optimization technique for sequential and parallel progra...
Almost every modern processor is designed with a memory hierarchy organized into several levels, eac...
42 pages, available as LIP research report RR-2009-15Numerical linear algebra and combinatorial opti...
In a recent paper it was shown how memory traffic can be diminished by reformulating the classic alg...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
This work investigates the problem of permuting a sparse rectangular matrix into block diagonal form...
We focus on two known NP-hard problems that have applications in sparse matrix computations: the env...
Efficient memory usage is crucial for data-intensive applications as a smaller memory footprint ensu...
The present work presents a strategy to increase the arithmetic intensity of the solvers. Namely, we...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
Combinatorial scientific computing plays an important enabling role in computational science, partic...
Large sparse symmetric matrix problems arise in a number of scientific and engineering fields such a...