Abstract: Nowadays, Hadoop is massively used to store large data generated by various sources. These data are often represented in large scale graphs to solve real world problems. To compute those ...

Abstract: Among the limitations of current quantum machines, the qubits count represents one of the most critical challenges for porting reasonably large computational problems, such as those coming ...

Erik Saule and Umit V. Catalytirek from Ohio State University have published a new paper examining the scalability of the upcoming Intel MIC architecture on Graph algorithms. Graph algorithms are ...

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

This GitHub project is a C implementation of the Greedy Graph Coloring Algorithm. The algorithm aims to color the vertices of an undirected graph in such a way that no two adjacent vertices share the ...

This project implements six graph coloring algorithms — ranging from simple greedy heuristics to a customized, improved Genetic Algorithm (GA). The goal is to show how heuristic design strongly ...

The graph colouring problem, a classic NP-hard challenge, is central to many practical applications such as scheduling, resource allocation and network management. Recent advances have seen the ...