Course: B649 Topics on Systems Graduate Cloud Computing Class

Project Details

Project Lead
Judy Qiu 
Project Manager
Judy Qiu 
Project Members
Pradnya Kakodkar  
Institution
Indiana University, School of Informatics and Computing  
Discipline
Computer Science (401) 

Abstract

A topics course on cloud computing with 27 graduate students at Masters and PhD level offered Fall 2010 as part of Computer Science curriculum

Intellectual Merit

Objectives This course will offer programming models and tools of cloud computing to support data intensive science applications. Students will get to know the latest research topics of cloud platforms and have the opportunity to understand some commercial cloud systems through projects using FutureGrid resources. Scope and topcis Several new computing paradigms are emerging from large commercial clouds. These include virtual machine based utility computing environments such as Amazon AWS and Microsoft Azure. Further there are also a set of new MapReduce programming paradigms coming from Information retrieval field which have been shown to be effective for scientific data analysis. These developments have been highlighted by a recent NSF CISE-OCI announcement of opportunities in this area. This class covers many of the key concepts with a common set of simple examples. It is designed to prepare participants to understand and compare capabilities of these new technologies and infrastructure and to have a basic idea as to how to get started. Particularly, the Big Data Workshop Website covers the background and topics of interest as below. Projects include Bioinformatics and Information retrieval

Broader Impacts

This material will generate curricula material that will be used to build up an online distributed systems/cloud resource

Scale of Use

Modest resources for each student

Results

See class web page http://salsahpc.indiana.edu/b649/
This class involved 27 Graduate students with a mix of Masters and PhD students and was offered fall 2010 as part of Indiana University Computer Science program. Many current FutureGrid experts went to this class which routinely used FutureGrid for student projects. Projects included

  • Hadoop

  • DryadLINQ/Dryad

  • Twister

  • Eucalyptus

  • Nimbus

  • Sector/Sphere

  • Virtual Appliances

  • Cloud Storage

  • Clustering by Deterministic Annealing (DAC)

  • Multi Dimensional Scaling (MDS)

  • Latent Dirichlet Allocation (LDA)