Main field(s) of study and in-depth level:
Computer Science A1N,
Computational Science A1N
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
The Faculty Board of Science and Technology
120 credits including Scientific Computing I. Computer Programming II or Imperative and Object-oriented Programming Methodology (programming in Java or Python). Also recommended are courses in parallel computing/programming, distributed systems and web applications.
use public and private cloud solutions for computational science and engineering applications;
discuss key concepts of cloud computing services, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS);
asses the suitability of cloud computing infrastructures for different scientific applications;
implement software for cloud-based distributed computing using the technology presented in the course;
critically analyse and present solutions and implementations in writing and orally.
An application oriented introduction to cloud computing. Basics of Service Oriented Architectures (SOA). Basic concepts of cloud computing such as virtualisation and the service layers IaaS, PaaS and SaaS, dynamic provisioning, elasticity. Practical use of available public and private cloud stacks. Introduction to cloud security. Task based programming in cloud environments, distributed task queues such as Celery. Message brokers such as RabbitMQ.
Lectures and tutorials, guest lectures, laboratory work. Participants work in groups as well as on individual basis.
Written assignments with oral presentation. Written and oral presentation of a software project. Active participation in seminars. Written and oral discussion of assignments and research papers.
week 18, 2018
Gannon, Dennis B. (professor Emeritus)
Cloud computing for science and engineering