Parallel Computer Architecture Clusters and Grids - NHE2530

Assessment 4: Oral presentation/assessment

Oral presentation/assessment

Assessment 3: Practice exam/test

Practice exam/test

Assessment 1: Quizzes / polls

Quizzes / polls

Assessment 2: Written practice exercise

Written practice exercise

Assessment 3: In-Class Test

Whole syllabus, unseen, closed book, on-line. Exam conditions apply.

In-Class Test

Assessment 1: Written Assignment

Taught material will contribute an element every week to the SAIL programme (Score As I Learn) submitted via the VLE platform. 11 x 15 minutes weekly assignments. Each assignment will be worth 3%. Taking the best 8 out of 11 scores.

Written Assignment

Assessment 2: Written Assignment

A report will present students’ results of practical work in deploying a computer cluster and evaluating a campus grid cluster performance using MPI parallel programs.

<p>In this module you will be introduced to Computer Cluster, Cloud and Grid technologies and applications. We will focus on the fundamental components of Cluster environments, such as Commodity Components for Clusters, Network Services/Communication software, Cluster Middleware, Resource management, and Parallel Programming Environments. You will study the components of Grid environments, such as Authentication, Authorization, Resource access, and Resource discovery. The hands-on laboratory exercises will provide the necessary practical experience with Cluster and Grid middleware software required to construct Cluster and Grid applications.</p>

Requirements apply to students taking an IET accredited course. Please refer to the Programme Specification Document for details.

School of Computing and Engineering

<p>https://library.hud.ac.uk/readinglists/NHE2530</p>

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Electrical Engineering

NHE2530 - Parallel Computer Architecture Clusters and Grids

Parallel Computer Architecture Clusters and Grids

Examine and compare the components of computer cluster and grid architectures, and assess their scalability, performance metrics and measures, and theoretical speed up of parallel processing applications.

Deploy a cluster, using COTS hardware components or in a cloud, using cluster middleware, resource and job management, and parallel programming environment software.

Understand the fundamental aspects of parallel and distributed processing.

Evaluate cluster and grid systems using appropriate software tools and benchmarks, in order to justify their applicability/non-applicability in running specific engineering or scientific application.