High Performance Computing and Big Data

6 EC

Semester 1, period 3

5284HPCB6Y

Owner Master Computer Science (joint degree)
Coordinator dr. A.S.Z. Belloum
Part of Master Computer Science (joint degree), track Big Data Engineering, year 1

Course manual 2018/2019

Course content

The course covers a number of key topics in the field of high performance computing and big data engineering. The course is organized as a lectures and workshops which help the students to develop both theoretical and practical skills. Following is the list of topics covers in the course:

  • Introduction to parallel programming models and Big Data
  • Grid/Cloud Computing
  • General-purpose graphics programing unit for Big Data Application
  • Big data processing: Apache Spark and storm
  • Relation BD and NoSQL, NewSQL
  • Data Intensive computing with Hadoop: MapReduce and Pig,
  • Local/Remote Visualisation for Data intensive application
  • HPC Cloud.

Study materials

Other

  • Course is based on Scientific publications and other Material available online

Objectives

Students will develop skills in High Performance Computing which are commonly used to solve Data intensive applications and avoid common pitfalls which often lead to misuse of valuable computing resources. In this course students will learn about:

  • Approaches used in HPC and distributed computing
  • Methods and techniques to solve Big Data problems
  • Develop skills to use HPC facilities and e-infrastructure

Teaching methods

  • Hoorcollege
  • Workshop

Learning activities

Activity

Number of hours

Hoorcollege

4

Laptopcollege

36

Zelfstudie

128

Assessment

Item and weight Details

Final grade

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Weeknummer Onderwerpen Studiestof
1
2
3
4
5
6
7
8

Timetable

The schedule for this course is published on DataNose.

Additional information

  • Recommended prior knowledge: Students must be able to program in Python, Java, and basic C (or be able to get the needed skills on the fly).
  • The  course is not suited for Computer Science students following the Big Data Engineering Track (overlap with Mandatory courses)
  • This is an elective course for which the students must seek the commitment of the Examination Board.
  • The course is composed of set of introductory lectures followed by workshops including hands-on. The workshops are organized by UvA researchers as well as guests from the national Supercomputing Centre (SURFsara). During these workshops, students will have access HPC facilities available at Surfsara (https://www.surfsara.nl/services/high-performance-computing).
  • (*) list of all available workshops can be found on the course web site: http://www.hpc.uva.nl/Workshops/

Contact information

Coordinator

  • dr. A.S.Z. Belloum