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/)
Summary of the processing resources on Amazon EC2 and the Abe high-performance clusterType
Architecture
CPU
Cores
Memory
Network
Storage
Price
Amazon EC2
ml.small
32-bit
2.0-2.6 GHz Opteron
1-2
1.7 GB
1 Gbps Ethernet
Local
$0.10/hr
ml.large
64-bit
2.0-2.6 GHz Opteron
2
7.5 GB
1 Gbps Ethernet
Local
$0.40/hr
ml.xlarge
64-bit
2.0-2.6 GHz Opteron
4
15 GB
1 Gbps Ethernet
Local
$0.80/hr
cl.medium
32-bit
2.33-2.66 GHz Xeon
2
1.7 GB
1 Gbps Ethernet
Local
$0.20/hr
cl.xlarge
64-bit
2.0-2.66 GHz Xeon
8
7.5 GB
1 Gbps Ethernet
Local
$0.80/hr
Abe Cluster
abe.local
64-bit
2.33 GHz Xeon
8
8 GB
10 Gbps InfiniBand
Local
N/A
abe.lustre
64-bit
2.33 GHz Xeon
8
8 GB
10 Gbps InfiniBand
Lustre TM
N/A
- 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
The workflow contained 10,429 tasks, read 4.2 GB of input data, and produced 7.9 GB of output data.
Montage is considered I/O-bound because it spends more than 95% of its time waiting on I/O operations. - 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
The workflow contained 320 tasks, read 6 GB of input data, and produced 160 MB of output data.
Broadband is considered memory-limited because more than 75% of its runtime is consumed by tasks requiring more than 1 GB of physical memory. - Epigenome (http://epigenome.usc.edu) from biochemistry: maps short DNA segments collected using high-throughput gene sequencing machines to a previously constructed reference genome
The workflow contained 81 tasks, read 1.8 GB of input data, and produced 300 MB of output data.
Epigenome is considered CPU-bound because it spends 99% of its runtime in the CPU and only 1% on I/O and other activities.
- Montage (http://montage.ipac.caltech.edu) from astronomy: a toolkit for aggregating astronomical images in Flexible Image Transport System (FITS) format into mosaic
-
- 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
- Summary of resource use by the workflow applications
- Methods
The experiments were all run on single nodes to provide an unbiased comparison of the performance of workflows on Amazon EC2 and Abe.
For experiments on EC2:- Executables were pre-installed in a Virtual Machine image which is deployed on the node.
- Input data was stored in the Amazon EBS.
- Output, intermediate files and the application executables were stored on local disks.
Cloud performance
Summary
Part II - Application to calculation of periodograms
References
- Berriman, G.B. et al. Sixth IEEE International Conference on e-Science, 1-7 (2010)
- Berriman, G.B. et al. SPIE Conference 7740: Software and Cyberinfrastructure for Astronomy (2010)
- Juve, G. et al. Cloud Computing Workshop in Conjunction with e-Science Oxford, UK: IEEE (2009)
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.