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  • Cost effectiveness study
    Cost calculations based on processing reqeusts for 36,000 mosaic of 2MASS images (Total size 10TB) of size 4 sq deg over a period of three years (typical workload for image mosaic service).
    Results show that Amazon EC2 is much less attractive than a local service for I/O-bound application due to the high costs of data storage in Amazon EC2.
    Tables below show the cost of both local and Amazon EC2 service.
    Cost per mosaic of a locally hosted image mosaic service

    Item

    Cost ($)

    12 TB RAID 5 disk farm and enclosure
    (3 yr support)

    12,000

    Dell 2650 Xeon quad-core processor,
    1 TB staging area

    5,000

    Power, cooling and administration

    6,000

    Total 3-year Cost

    23,000

    Cost per mosaic

    0.64

    Cost per mosaic of a mosaic service hosted in the Amazon EC2 cloud

    Item

    Cost ($)

    Network Transfer In

    1000

    Data Storage on Elastic Block Storage

    36,000

    Processor Cost (cl.medium)

    4,500

    I/O operations

    7,000

    Network Transfer Out

    4,200

    Total 3-year Cost

    52,700

    Cost per mosaic

    1.46

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Part II - Application to calculation of periodograms

Generation of a science product: an atlas of periodograms for the 210,000 light curves released by the NASA Kepler Mission.

Summary of periodogram calculations on the Amazon EC2 cloud

 

 

Result

Runtimes

Tasks

631,992

 

Mean Task Runtime

6.34 sec

 

Jobs

25,401

 

Mean Job Runtime

2.62 min

 

Total CPU Time

1,113 hr

 

Total Wall Time

26.8 hr

Inputs

Input Files

210,664

 

Mean Input Size

0.084 MB

 

Total Input Size

17.3 GB

Outputs

Output Files

1,263,984

 

Mean Output Size

0.124 MB

 

Total Output Size

76.52 GB

Cost

Compute Cost

$291.58

 

Transfer Cost

$11.48

 

Total Cost

$303.06

References

  1. Berriman, G.B. et al. Sixth IEEE International Conference on e-Science, 1-7 (2010)
  2. Berriman, G.B. et al. SPIE Conference 7740: Software and Cyberinfrastructure for Astronomy (2010)
  3. Juve, G. et al. Cloud Computing Workshop in Conjunction with e-Science Oxford, UK: IEEE (2009)

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