Distributed Computing for e-Science 1 (P01343)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : PHY-P-DCE1

The focus of this course is the use of distributed computing technologies, such as the Grid, in support of e-Science. It covers the principles and applications of e-Science methods and the distributed computing systems that underpin them, with a practical introduction to the use of some of those systems. The course delivery will comprise a small number of whole-day sessions, which combine lecture material covering the principles in a particular topic, together with hands-on exercises which illustrate particular applications of those principles and which will often be continued in private study time. The topics covered in this way are security, portals, computation and data manipulation. A wider appreciation of the variety of current realisations of distributed computing within e-Science will be achieved through investigation of case-studies for an essay, supported by some lecture material.

Entry Requirements

? This course is not available to visting students.

? Pre-requisites : Only postgraduates or final year MPhys students with suitable computational background, subject to space restrictions and agreement with relevant Programme Coordinator.

Subject Areas

Home subject area

Postgraduate (School of Physics), (School of Physics, Schedule Q)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 1 (Blocks 1-2)

? Contact Teaching Time : 6 hour(s) per week for 4 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
20/09/2006	10:00	17:00	Room 7.7307, JCMB	KB

All of the following classes

Type	Day	Start	End	Area
Lecture	Wednesday	10:00	13:00	KB
Lecture	Wednesday	15:00	17:00	KB

Summary of Intended Learning Outcomes

On completion of this course, students should be able to

• Describe the nature of e-Science, its associated technical and organisational requirements, and the range of applications to which e-Science technologies are applicable.
• Show knowledge of current major e-Science projects and an appreciation of the design of production e-Science infrastructures.
• Demonstrate an understanding of the overall architectures and functionalities of selected middleware products commonly used in e-Science and of the standards which they implement.
• Define and successfully deploy computational jobs and data manipulation tasks utilising remote and distributed resources.