The primary purpose of this paper is to provide an in-depth analysis of different platforms
available for performing big data analytics. This paper surveys different hardware platforms …

Computing subgraph frequencies is a fundamental task that lies at the core of several
network analysis methodologies, such as network motifs and graphlet-based metrics, which …

Prior work has shown dramatic acceleration for various database operations on GPUs, but
only using primitives that are not part of conventional database languages such as SQL …

Disaster caused by both nature and human factors has resulted in the occurrence of human
casualties, environmental damage, property loss, and psychological impact. The study aims …

General purpose computation using Graphic Processing Units (GPUs) is a well‐established
research area focusing on high‐performance computing solutions for massively …

Cluster analysis plays a critical role in a wide variety of applications; but it is now facing the
computational challenge due to the continuously increasing data volume. Parallel …

Frequent Itemsets and Association Rules Mining (FIM) is a key task in knowledge discovery
from data. As the dataset grows, the cost of solving this task is dominated by the component …

We design and implement Mars, a MapReduce runtime system accelerated with graphics
processing units (GPUs). MapReduce is a simple and flexible parallel programming …

The KNN algorithm is a widely applied method for classification in machine learning and
pattern recognition. However, we can't be able to get a satisfactory performance in many …

Recently there has been a lot of interest in graph-based analysis. One of the most important
aspects of graph-based analysis is to measure similarity between nodes in a graph …