Overview
Story 1 A study of cost and performance of the application of cloud computing to Astronomy 1
The performance of three workflow applications with different I/O, memory and CPU requirements are investigated on Amazon EC2 and the performance of cloud are compared with that of a typical HPC (Abe in NCSA).
The goal is to determine which type of scientific workflow applications are cheaply and efficiently run on the Amazon EC2 cloud.
Also the application of cloud computing to the generation of an atlas of periodograms for the 210,000 light curves is described.
Part I - Performance of three workflow applications
Tools and methods
- Cloud platform: Amazon EC2 (http://aws.amazon.com/ec2/)
- Workflow a applications
Three different workflow applications are chosen.- Montage (http://montage.ipac.caltech.edu) from astronomy: a toolkit for aggregating astronomical images in Flexible Image Transport System (FITS) format into mosaic
- Broadband (http://scec.usc.edu/research/cme) from seismology: generates and compares intensity measures of seismograms from several high- and low-frequency earthquake simulation codes
- Epigenome (http://epigenome.usc.edu) from biochemistry: maps short DNA segments collected using high-throughput gene sequencing machines to a previously constructed reference genome
- Summary of resource use by the workflow applications
Application
I/O
Memory
CPU
Montage
High
Low
Low
Broadband
Medium
High
Medium
Epigenome
Low
Medium
High
- Methods
Cloud performance
Summary
Part II - Application to calculation of periodograms
References
Notes and other links
a. Workflow: loosely coupled parallel applications that consist of a set of computational tasks linked by data- and control-flow dependencies.