Add to ORKGWe study the relationship between the design and analysis of graph algorithms in the coarsed grained parallel models and the behavior of the resulting code on clusters. We conclude that the coarse grained multicomputer model (CGM) is well suited to design competitive algorithms, and that it is thereby now possible to aim to develop portable, predictable and efficient parallel code for graph problems on clusters
In this paper, we present CGMgraph, the first integrated library of parallel graph methods for PC cl...
library of parallel graph methods for PC clusters based on Coarse Grained Multicomputer (CGM) algori...
La résolution de grands systèmes linéaires creux est un élément essentiel des simulations numériques...
We study the relationship between the design and analysis of graph algorithms in the coarsed grained...
We study the relationship between the design and analysis of graph algorithms in the coarsed grained...
We present the first efficient algorithm for a coarse grained multiprocessor that colors a graph $G$...
We present two algorithms for the List Ranking Problem in the Coarse Grained Multicomputer model (CG...
E. C'aceres 1 , F. Dehne 2 , A. Ferreira 3 , P. Flocchini 4 , I. Rieping 5 , A. Ronca...
Efficiently processing large graphs is challenging, since parallel graph algorithms suffer from poor...
In this paper we present deterministic parallel algorithms for the coarse-grained multicomputer (CGM...
AbstractWe present an efficient and scalable coarse grained multicomputer (CGM) coloring algorithm t...
In this paper, we present deterministic parallel algorithms for the coarse grained multicomputer (CG...
Agglomerative clustering is an effective greedy way to quickly generate graph clusterings of high mo...
Colloque avec actes et comité de lecture. internationale.International audienceWe report on experime...
Colloque avec actes et comité de lecture. internationale.International audienceWe present experiment...
In this paper, we present CGMgraph, the first integrated library of parallel graph methods for PC cl...
library of parallel graph methods for PC clusters based on Coarse Grained Multicomputer (CGM) algori...
La résolution de grands systèmes linéaires creux est un élément essentiel des simulations numériques...
We study the relationship between the design and analysis of graph algorithms in the coarsed grained...
We study the relationship between the design and analysis of graph algorithms in the coarsed grained...
We present the first efficient algorithm for a coarse grained multiprocessor that colors a graph $G$...
We present two algorithms for the List Ranking Problem in the Coarse Grained Multicomputer model (CG...
E. C'aceres 1 , F. Dehne 2 , A. Ferreira 3 , P. Flocchini 4 , I. Rieping 5 , A. Ronca...
Efficiently processing large graphs is challenging, since parallel graph algorithms suffer from poor...
In this paper we present deterministic parallel algorithms for the coarse-grained multicomputer (CGM...
AbstractWe present an efficient and scalable coarse grained multicomputer (CGM) coloring algorithm t...
In this paper, we present deterministic parallel algorithms for the coarse grained multicomputer (CG...
Agglomerative clustering is an effective greedy way to quickly generate graph clusterings of high mo...
Colloque avec actes et comité de lecture. internationale.International audienceWe report on experime...
Colloque avec actes et comité de lecture. internationale.International audienceWe present experiment...
In this paper, we present CGMgraph, the first integrated library of parallel graph methods for PC cl...
library of parallel graph methods for PC clusters based on Coarse Grained Multicomputer (CGM) algori...
La résolution de grands systèmes linéaires creux est un élément essentiel des simulations numériques...