Some examples of parallel computing applications are weather forecasting, computational fluid dynamics, molecular dynamics, image processing, and machine learning. Distributed computing involves ...

When dealing with issues requiring fault tolerance, regional data localization, or horizontal scalability, distributed systems coordinate numerous machines. Parallel computing suits simulation ...

DISTRIBUTED SYSTEMS AND PARALLEL COMPUTING Optimizing Bicubic Interpolation for Image Processing In this project, we investigated the performance of bicubic interpolation against nearest neighbor ...

Our group works in the broad area of Parallel & Distributed Computing with focus on issues related to Programmability, Performance, Scalability and Fault Tolerance. We build smart scalable systems to ...

Welcome to my Parallel ... of parallel and distributed computing. Whether you're a beginner or looking to delve into more complex topics, this repository provides hands-on experience with ...

The two most popular technologies, Distributed Parallel Processing (DPP) and Cloud Computing (CC) rely on the clarity of solving the user's problem in this method. The proposed system has been built ...

Abstract: In order to process complex and large-scale graph data numerous distributed graph-parallel computing platforms have been proposed. However, excessive communications among computing nodes in ...

Distributed systems facilitate sharing different resources and capabilities, to provide users with a single and integrated coherent network. The opposite of a distributed system is a centralized ...

Researchers in PDCL are devoted to investigating the theory, design, evaluation, and use of parallel and distributed computing systems. Current research activities in PDCL can be broadly grouped into ...