There are great challenges in performing graph coloring on GPU in general. First, the long-
tail problem exists in the recursion algorithm because the conflict (ie, different threads assign …

Community detection algorithms try to identify the underlying community structure (ie, clearly
distinguishable closely interacting groups of vertices) in a graph representing complex …

The design and implementation of parallel algorithms for dynamic graph problems is
attracting significant research attention in the recent years, driven by numerous applications …

PageRank algorithm is a benchmark for many graph analytics and is the underlying kernel
for link predictions, recommendation systems. It is an iterative algorithm that updates ranks …

This paper proposes software-defined floating-point number formats for graph processing
workloads, which can improve performance in irregular workloads by reducing cache …

PageRank is a graph centrality metric that gives the importance of each node in a given
graph. The PageRank algorithm provides important insights to understand the behavior of …

ReRAM-based Processing-in-Memory (PIM) offers a promising paradigm for computing near
data, making it an attractive platform of choice for graph applications that suffer from sparsity …

Approximate computing techniques, where less-than-perfect solutions are acceptable,
present performance-accuracy trade-offs by performing inexact computations. Moreover …

The notion of networks is inherent in the structure, function and behavior of the natural and
engineered world that surround us. Consequently, graph models and methods have …

Smart health monitoring devices, known as Wireless Body Sensor Nodes (WBSN) are
transforming today's health-care landscape, shifting it from traditional hospital-based …