Related papers: Building and Installing a Hadoop/MapReduce Cluster…
In this paper, a technology for massive data storage and computing named Hadoop is surveyed. Hadoop consists of heterogeneous computing devices like regular PCs abstracting away the details of parallel processing and developers can just…
Hadoop is an open source implementation of the MapReduce Framework in the realm of distributed processing. A Hadoop cluster is a unique type of computational cluster designed for storing and analyzing large data sets across cluster of…
MapReduce is a technique used to vastly improve distributed processing of data and can massively speed up computation. Hadoop and its MapReduce relies on JVM and Java which is expensive on memory. High Performance Computing based MapReduce…
Storage systems are essential building blocks for cloud computing infrastructures. Although high performance storage servers are the ultimate solution for cloud storage, the implementation of inexpensive storage system remains an open…
The openPC is a set of open source tools that realizes a parallel machine and distributed computing environment divisible into several independent blocks of nodes, and each of them is remotely but fully in any means accessible for users…
The emergence of cloud computing has enabled an incredible growth in available hardware resources at very low costs. These resources are being increasingly utilized by corporations for scalable analysis of "big data" problems. In this work,…
Nowadays most of the cloud applications process large amount of data to provide the desired results. Data volumes to be processed by cloud applications are growing much faster than computing power. This growth demands new strategies for…
Solving the software dependency issue under the HPC environment has always been a difficult task for both computing system administrators and application scientists. This work would like to tackle the issue by introducing the modern…
Applications like Big Data, Machine Learning, Deep Learning and even other Engineering and Scientific research requires a lot of computing power; making High-Performance Computing (HPC) an important field. But access to Supercomputers is…
Using barebone PC components and NIC's, we construct a linux cluster which has 2-dimensional mesh structure. This cluster has smaller footprint, is less expensive, and use less power compared to conventional linux cluster. Here, we report…
Deploying, configuring, and managing large clusters is very a demanding and cumbersome task due to the complexity of such systems and the variety of skills needed. One needs to perform low-level configuration of the cluster nodes to ensure…
This study explores strategies for academic researchers to optimize computational resources within limited budgets, focusing on building small, efficient computing clusters. It delves into the comparative costs of purchasing versus renting…
High-throughput computing projects require the solution of large numbers of problems. In many cases, these problems can be solved on desktop PCs, or can be broken down into independent "PC-solvable" sub-problems. In such cases, the projects…
Analyzing and working with big data could be very diffi cult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with…
MapReduce (MR) is the most popular solution to build applications for large-scale data processing. These applications are often deployed on large clusters of commodity machines, where failures happen constantly due to bugs, hardware…
We present our ongoing work building a Raspberry Pi cluster consisting of 300 nodes. The unique characteristics of this single board computer pose several challenges, but also offer a number of interesting opportunities. On the one hand, a…
MapReduce, the popular programming paradigm for large-scale data processing, has traditionally been deployed over tightly-coupled clusters where the data is already locally available. The assumption that the data and compute resources are…
Programming a distributed system, such as a cluster, requires extended use of low-level communication libraries and can often become cumbersome and error prone for the average developer. In this work, we consider each node of a cluster as a…
In this report we investigate the performance of Hadoop clusters, deployed with separated storage and compute layers, on top of a hypervisor managing a single physical host. We have analyzed and evaluated the different Hadoop cluster…
Small Beowulf clusters can effectively serve as personal or group supercomputers. In such an environment, a cluster can be optimally designed for a specific problem (or a small set of codes). We discuss how theoretical analysis of the code…