In the modern-day era of technology, a paradigm shift has been witnessed in the areas
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …

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

The immense amount of data created by digitalization requires parallel computing for
machine-learning methods. While there are many parallel implementations for support …

Many bioinformatics applications that analyse large volumes of high-dimensional data
comprise complex problems requiring metaheuristics approaches with different types of …

This chapter discusses modern methods of data processing, especially data parallelization
and data processing by bio-inspired methods. The synthesis of novel methods is performed …

In this paper we present new results obtained by a competitive game based distributed
geometry decomposition method (GDM) for graphics processing unit (GPU) assisted shape …

The present trend in the development of computer architectures that offer improvements in
both performance and energy efficiency has provided clusters with interconnected nodes …

Present heterogeneous architectures interconnect nodes including multiple multi-core
microprocessors and accelerators that allow different strategies to accelerate the …

Abstract Frequent Itemset Mining (FIM) is one of the most investigated fields of data mining.
The goal of Frequent Itemset Mining (FIM) is to find the most frequently-occurring subsets …

We propose a scheme for efficient set similarity joins on Graphics Processing Units (GPUs).
Due to the rapid growth and diversification of data, there is an increasing demand for fast …