Topics
multicomputerProgramming language
We 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
library of parallel graph methods for PC clusters based on Coarse Grained Multicomputer (CGM) algori...
There has been significant recent interest in parallel graph processing due to the need to quickly a...
Future High Performance Computing (HPC) nodes will have many more processors than the contemporary a...
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...
In this paper, we present deterministic parallel algorithms for the coarse grained multicomputer (CG...
AbstractWe present an efficient and scalable coarse grained multicomputer (CGM) coloring algorithm t...
Colloque avec actes et comité de lecture. internationale.International audienceWe report on experime...
Agglomerative clustering is an effective greedy way to quickly generate graph clusterings of high mo...
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...
There has been significant recent interest in parallel graph processing due to the need to quickly a...
Future High Performance Computing (HPC) nodes will have many more processors than the contemporary a...
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...
In this paper, we present deterministic parallel algorithms for the coarse grained multicomputer (CG...
AbstractWe present an efficient and scalable coarse grained multicomputer (CGM) coloring algorithm t...
Colloque avec actes et comité de lecture. internationale.International audienceWe report on experime...
Agglomerative clustering is an effective greedy way to quickly generate graph clusterings of high mo...
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...
There has been significant recent interest in parallel graph processing due to the need to quickly a...
Future High Performance Computing (HPC) nodes will have many more processors than the contemporary a...
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