An implementation of a newly developed parallel graph traversal algorithm on a new one-chip many-core structure with a MapReduce architecture is presented. The generic structure's main features and performances are described. The developed algorithm uses the representation of the graph as a matrix and the new MapReduce structure performs best on matrix-vector operations so, the algorithm considers both, dense and sparse matrix cases. A Verilog based simulator is used for evaluation. The main outcome of the presented research is that our MapReduce architecture (with P execution units and the size in O(P)) has the same theoretical time performance: O(NlogN) for P = N = |V | = number of vertices in the graph, as the hypercube architecture (hav...
Abstract—Processing large graphs is becoming increasingly important for many domains such as social ...
Many emerging large-scale data science applications require searching large graphs dis-tributed acro...
International audienceAdvances in processing power and memory technology have made multicore compute...
Abstract—Breadth-First Search is a graph traversal technique used in many applications as a building...
Abstract—The construction of efficient parallel graph al-gorithms is important for quickly solving p...
Data-intensive, graph-based computations are pervasive in several scientific applications, and are k...
In this chapter, we study the problem of traversing large graphs. A traversal, a systematic method o...
pre-printFast, scalable, low-cost, and low-power execution of parallel graph algorithms is important...
With the increasing processing power of multicore computers, parallel graph search (or graph travers...
Breadth First Search Traversal algorithm is an important kernel for many real - time ...
Parallel graph algorithms have become one of the principal applications of high-performance computin...
Graph abstractions are extensively used to understand and solve challenging computational problems i...
Abstract—Optimized GPU kernels are sufficiently complicated to write that they often are specialized...
Breadth-first search (BFS) is an essential graph traversal strategy widely used in many computing ...
Breadth-First Search (BFS) is a graph traversal technique used in many applications as a building bl...
Abstract—Processing large graphs is becoming increasingly important for many domains such as social ...
Many emerging large-scale data science applications require searching large graphs dis-tributed acro...
International audienceAdvances in processing power and memory technology have made multicore compute...
Abstract—Breadth-First Search is a graph traversal technique used in many applications as a building...
Abstract—The construction of efficient parallel graph al-gorithms is important for quickly solving p...
Data-intensive, graph-based computations are pervasive in several scientific applications, and are k...
In this chapter, we study the problem of traversing large graphs. A traversal, a systematic method o...
pre-printFast, scalable, low-cost, and low-power execution of parallel graph algorithms is important...
With the increasing processing power of multicore computers, parallel graph search (or graph travers...
Breadth First Search Traversal algorithm is an important kernel for many real - time ...
Parallel graph algorithms have become one of the principal applications of high-performance computin...
Graph abstractions are extensively used to understand and solve challenging computational problems i...
Abstract—Optimized GPU kernels are sufficiently complicated to write that they often are specialized...
Breadth-first search (BFS) is an essential graph traversal strategy widely used in many computing ...
Breadth-First Search (BFS) is a graph traversal technique used in many applications as a building bl...
Abstract—Processing large graphs is becoming increasingly important for many domains such as social ...
Many emerging large-scale data science applications require searching large graphs dis-tributed acro...
International audienceAdvances in processing power and memory technology have made multicore compute...