Section outline

  • Module Overview

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    Course summary 

    This course is intended as an introduction to computational grids, why we need them, who will use them, the basic services that must be provided by the grid infrastructure.,

    The course would compliment Cluster Computing and also Parallel and Distributed Programming and represent a third course in a sequence suitable for research in cluster and meta-cluster design, administration and programming.

    Module learning outcomes: 

    At the end of this course, the you re able to:

    1. Explain the fundamental principles and architecture of grid computing. 
    2. Apply grid computing concepts to design effective distributed computing environments. 
    3. Analyze failures in grid systems and develop appropriate preventive and risk‑management strategies. 
    4. Demonstrate practical competence in using grid computing tools and technologies. 
    5. Utilize ICT tools efficiently to manage time and resources in grid computing projects. 

    Indicative content:

    Unit1: Overview and Motivation: Introduction To Grids, Need of computational grids, potential users and techniques for use of grids. Grid requirements of end users, application developers, tool developers, grid developers, and system managers.

    Unit2: Grid Architecture: Networking Infrastructure, Protocols and Quality of Service - Computing Platforms, Operating Systems and Network Interfaces - Compilers, Languages and Libraries for the Grid - Grid Scheduling, Resource Management, Resource Brokers, Resource Reservations - Instrumentation and Measurement, Performance Analysis and Visualization - Security, Accounting and Assurance

    Unit3: Grid Community Toolkit (GCT): Core systems and related tools such as the Message Passing Interface communication library, the Remote I/O (RIO) library, and the Nimrod parameter study library - Legion and related software - Condor and the Grid - Open Grid Service Architecture and Data Grids - Grid Portal Development - Application Types: geographically distributed, high-throughput, on demand, collaborative, and data intensive supercomputing, computational steering, real-time access to distributed instrumentation systems.

    Mode of teaching and learning

    This module will be taught in blended mode. This means 30% of the content will be delivered online using the eLearning platform, while 70% will be face-to-face. 

    Assessment strategy

    1. Each unit will be assessed online using quizzes and assignments.
    2. One Continuous Assessment Test (CAT)
    3. One project
    4. One final exam

    Completion criteria:

    Successful completion criteria include:

    • Active participation and engagement: Regular contributions to discussions, forums, and group activities, demonstrating critical thinking and collaboration.
    • Timely completion of assignments: Submitting all tasks, projects, and assessments on or before deadlines, showing a thorough understanding of the material.
    • Achievement of learning outcomes: Meeting or exceeding the learning objectives set for the module, as measured by assessments, quizzes, or project outcomes.

    Tips to be a successful learner:

    At least four tips for you to succeed in this module:

    1. Set a consistent schedule: Dedicate specific times each day or week for coursework, and stick to this routine. Consistency helps manage time effectively and ensures you stay on track with assignments and readings.
    2. Engage actively in discussions: Participate regularly in online forums and group discussions. Sharing insights and asking questions not only enhances your understanding but also builds a supportive learning community.
    3. Apply what you learn immediately: Whenever possible, try to implement new strategies or tools in your classroom as you learn them. This practical application helps solidify concepts and demonstrates the value of the module in real-world settings.
    4. Seek support when needed: Don’t hesitate to reach out to your peers or facilitators or school IT officer in your school or any person at your home  if you encounter difficulties. Online learning can feel isolating, but building connections and asking for help can make the experience more collaborative and effective.

    Instructors:

    Name: Dr. Ntalindwa Theoneste

    Email: ntatheos@yahoo.co.uk / t.ntalindwa@ur.ac.rw

    Tel: 0788884594

    Copyright

    This material is licensed under an Attribution-Non-Commercial-Share Alike Creative Commons License. This means that you can remix, tweak, and build upon the work non-commercially,  if you credit this work and license your new creations under identical terms. 

    How to access the course:

    Module Code: COE4261
    Access Key: COEY42015

  • Unit 1. 1: Overview and Motivation

    Learning Outcomes:

    By the end of this unit, you are able to:

    1. Explain the concept of computational grids and justify the need for grid computing by discussing its motivations, advantages, and typical application areas.

    2. Identify potential users of computational grids and describe the key techniques used in grid environments for effective resource sharing and problem solving.

    3. Analyze and differentiate the requirements of various grid stakeholders, including end users, application developers, tool developers, grid developers, and system managers, in the design and use of grid systems.

  • Unit 1. 2: Grid terms and concepts

    In this Section we introduce a few key grid terms and concepts that we use
    throughout this module. 

    At the end of this unit, you are able to:

    • Understand and be able to define key grid terms.
    • Explain how major grid components work together.
    • Use basic grid concepts to interpret simple power system scenarios.

  • Unit 1.3. Grid user roles

    This Unit briefly describes grid computing from the perspectives of the user and the administrator. The architect and application developer are other key roles in a grid environment.

    At the end of this unit, you are able to:

    1. Understand what grid computing is and how it is used.
    2. Describe the roles of users and administrators in a grid environment.
    3. Recognize that architects and developers also play key roles, which are introduced in later chapters.

  • Unit2: Grid Architecture

    At the end of this unit, students will be able to:

    1. Define key components of grid computing, including GRAM, MDS, GASS, and GSI.

    2. Explain how grid computing works, describing the interactions between control nodes, providers, and users.

    3. Apply their knowledge to identify appropriate use cases for computational grids, scavenging grids, and data grids.

  • Unit3: Grid Community Toolkit (GCT)

    At the end of this unit, you are able to:
    1. Recall the main components and functions of the Globus Toolkit.
    2. Explain how grid protocols such as GSI, GRAM, and GridFTP support secure and efficient grid computing.
    3. Use Grid Information Services tools (e.g., LDAP queries) to discover and interpret resource information in a grid environment.
    4. Analyze how Globus Toolkit components interact to enable resource management, data transfer, and security across distributed systems.
    5. Evaluate the effectiveness of Globus Toolkit services in addressing challenges of scalability, heterogeneity, and security in grid computing.