We present the results obtained by using an evolution of our CUDA-based solution for the exploration, via a Breadth First Search, of large graphs. This latest version exploits at its best the features of the Ke-pler architecture and relies on a 2D decomposition of the adjacency matrix to reduce the number of communications among the GPUs. The final result is a code that can visit 400 billion edges in a second by using a cluster equipped with 4096 Tesla K20X GPUs.
We present the most recent release of our parallel implementation of the BFS and BC algorithms for t...
Abstract. Large graphs involving millions of vertices are common in many prac-tical applications and...
Gao, Guang R.Analysis of massive graphs has emerged as an important area for massively parallel comp...
Many emerging large-scale data science applications require searching large graphs dis-tributed acro...
Breadth-first search (BFS) is one of the most common graph traversal algorithms and the building blo...
On a GPU cluster, the ratio of high computing power to communication bandwidth makes scaling breadth...
There is growing interest in studying large scale graphs having millions of vertices and billions of...
Abstract—Optimized GPU kernels are sufficiently complicated to write that they often are specialized...
Data-intensive, graph-based computations are pervasive in several scientific applications, and are k...
pre-printFast, scalable, low-cost, and low-power execution of parallel graph algorithms is important...
When working on graphs, reachability is among the most common problems to address, since it is the b...
Abstract—The construction of efficient parallel graph al-gorithms is important for quickly solving p...
Parallel graph algorithms have become one of the principal applications of high-performance computin...
An implementation of a newly developed parallel graph traversal algorithm on a new one-chip many-cor...
With the increasing processing power of multicore computers, parallel graph search (or graph travers...
We present the most recent release of our parallel implementation of the BFS and BC algorithms for t...
Abstract. Large graphs involving millions of vertices are common in many prac-tical applications and...
Gao, Guang R.Analysis of massive graphs has emerged as an important area for massively parallel comp...
Many emerging large-scale data science applications require searching large graphs dis-tributed acro...
Breadth-first search (BFS) is one of the most common graph traversal algorithms and the building blo...
On a GPU cluster, the ratio of high computing power to communication bandwidth makes scaling breadth...
There is growing interest in studying large scale graphs having millions of vertices and billions of...
Abstract—Optimized GPU kernels are sufficiently complicated to write that they often are specialized...
Data-intensive, graph-based computations are pervasive in several scientific applications, and are k...
pre-printFast, scalable, low-cost, and low-power execution of parallel graph algorithms is important...
When working on graphs, reachability is among the most common problems to address, since it is the b...
Abstract—The construction of efficient parallel graph al-gorithms is important for quickly solving p...
Parallel graph algorithms have become one of the principal applications of high-performance computin...
An implementation of a newly developed parallel graph traversal algorithm on a new one-chip many-cor...
With the increasing processing power of multicore computers, parallel graph search (or graph travers...
We present the most recent release of our parallel implementation of the BFS and BC algorithms for t...
Abstract. Large graphs involving millions of vertices are common in many prac-tical applications and...
Gao, Guang R.Analysis of massive graphs has emerged as an important area for massively parallel comp...