Scalable parallel computing is essential for processing large scale-free (power-law) graphs. The distribution of data across processes becomes important on distributed-memory com-puters with thousands of cores. It has been shown that two-dimensional layouts (edge partitioning) can have significant advantages over traditional one-dimensional layouts. How-ever, simple 2D block distribution does not use the struc-ture of the graph, and more advanced 2D partitioning meth-ods are too expensive for large graphs. We propose a new two-dimensional partitioning algorithm that combines graph partitioning with 2D block distribution. The computational cost of the algorithm is essentially the same as 1D graph par-titioning. We study the performance of sp...
Abstract. Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performan...
Balanced graph partitioning is an NP-complete problem with a wide range of applications. These appli...
Balanced graph partitioning is anNP-complete problemwith a wide range of applications. These applica...
Graph partitioning is often used for load balancing in parallel computing, but it is known that hype...
Sparse matrix-vector multiplication is the kernel for many scientific computations. Parallelizing th...
International audienceWe investigate one dimensional partitioning of sparse matrices under a given o...
We present a new hyper graph-based method, the medium-grain method, for solving the sparse matrix pa...
We consider two-dimensional partitioning of general sparse matrices for parallel sparse matrix-vecto...
Abstract. Generalized sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many hi...
We investigate outer-product--parallel, inner-product--parallel, and row-by-row-product--parallel fo...
In this paper we present a parallel formulation of the multilevel graph partitioning and sparse matr...
International audienceWe propose a novel sparse matrix partitioning scheme, called semi-two-dimensio...
Graph Partitioning is an important load balancing problem in parallel processing. The simplest case ...
Abstract—We present techniques to process large scale-free graphs in distributed memory. Our aim is ...
A common operation in scientific computing is the multiplication of a sparse, rectangular or structu...
Abstract. Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performan...
Balanced graph partitioning is an NP-complete problem with a wide range of applications. These appli...
Balanced graph partitioning is anNP-complete problemwith a wide range of applications. These applica...
Graph partitioning is often used for load balancing in parallel computing, but it is known that hype...
Sparse matrix-vector multiplication is the kernel for many scientific computations. Parallelizing th...
International audienceWe investigate one dimensional partitioning of sparse matrices under a given o...
We present a new hyper graph-based method, the medium-grain method, for solving the sparse matrix pa...
We consider two-dimensional partitioning of general sparse matrices for parallel sparse matrix-vecto...
Abstract. Generalized sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many hi...
We investigate outer-product--parallel, inner-product--parallel, and row-by-row-product--parallel fo...
In this paper we present a parallel formulation of the multilevel graph partitioning and sparse matr...
International audienceWe propose a novel sparse matrix partitioning scheme, called semi-two-dimensio...
Graph Partitioning is an important load balancing problem in parallel processing. The simplest case ...
Abstract—We present techniques to process large scale-free graphs in distributed memory. Our aim is ...
A common operation in scientific computing is the multiplication of a sparse, rectangular or structu...
Abstract. Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performan...
Balanced graph partitioning is an NP-complete problem with a wide range of applications. These appli...
Balanced graph partitioning is anNP-complete problemwith a wide range of applications. These applica...