Cloud Computing for the Automated Assignment of Broadband Rotational

Spectra: Porting Autofit to Amazon EC2A thesis by Aaron C. Olinger

0 5 10 15 200

5

10

15

20

Number of Instances

Spee

d up

Fac

tor

Autofit: Fitting rotational Spectra [2]

[1]: Phillips, M., Pruning Interstellar Space: Rotational Spectroscopy of Small Organic Molecules. Senior Thesis, New College of Florida (2013)[2]: N.A. Seifert, I.A. Finneran, C. Perez, D.P. Zaleski, J.L. Neill, A.L. Steber, R.D. Suenram, A. Lesarri, S.T. Shipman, B.H. Pate, “Autofit, an Automated Fitting Tool for Broadband Rotational Spectra, and Applications to 1-Hexanal”, Journal of Molecular Spectroscopy (2015)

[1]

Distributed Computing

DistributorAlgorithm

Server

Client ClientClient

App AppApp

Cloud Computing

  vCPU ECU Memory (GiB)

Instance Storage (GB)

Linux/Unix Usage

General Purpose – Current Generation

t2.micro 1 Variable 1 EBS Only $0.013

m3.mediu

m

1 3 3.75 1 x 4 SSD $0.070

m3.large 2 6.5 7.5 1 x 32 SSD $0.140

m3.xlarge 4 13 15 2 x 40 SSD $0.280

m3.2xlarge 8 29 30 2 x 80 SSD $0.560

  vCPU ECU Memory (GiB)

Instance Storage (GB)

Linux/Unix Usage

Compute Optimized – Current generation

c4.large 2 8 3.75 EBS Only $0.116

c4.xlarge 4 16 7.5 EBS Only $0.232

c4.8xlarge 36 132 60 EBS Only $1.856

c3.large 2 7 3.75 2 x 16 SSD $0.105

c3.8xlarge 32 108 60 2 x 320 SSD $1.680

• Rates charged at the start of each hour

[1]

[1]

[1]: Amazon Web Services. Instance Types. http://aws.amazon.com/ec2/instance-types/ (Accessed May 5, 2015)

Creating the Distribution Network

Performance t2.micro

0 5 10 15 20 25 30 3505

101520253035

t2.micro Speed up factor and Ideal

Speed Up FactorIdeal Parallelization

Number of Instances

Spee

d up

Fac

tor

0 5 10 15 20 25 30 35 400

100200300400500600

700 t2.micro Time to Complete

Trial 1Trial 2Trial 3Trial 4

Number of Instances

Tim

e to

Com

plet

e(s)

  vCPU ECU Memory (GiB) Instance Storage (GB) Linux/Unix Usage

General Purpose – Current Generation

t2.micro 1 Variable 1 EBS Only $0.013 +750hr FREE per month

Performance c4.large

0 5 10 15 200

100

200

300

400

500

600

f(x) = 520.851888670618 x^-0.877354094684018R² = 0.996683951187583

c4.large mean completion time

Instances

Tim

e to

Com

plet

e (s

)

0 5 10 15 200

5

10

15

20

c4.large Speed up factor and Ideal

Speed Up FactorIdeal Parallelization

Number of Instances

Spee

d up

Fac

tor

Time to complete on Desktop (s)

Time to complete on

Laptop (s)

Time to complete on

Desktop (minutes)

Time to complete on

Laptop (minutes)

mean 600 1595 10 26.6standard deviation 35 32 0.58 0.53

  vCPU ECU Memory (GiB) Instance Storage (GB) Linux/Unix Usage

Compute Optimized – Current generation

c4.large 2 8 3.75 EBS Only $0.116

Cost Analysis0 5 10 15 20

8

9

10

11

12

13

14

15

Predicted Cost for 3 Day Job Using c4.large Instances

Instances running

Cos

t ($)

  vCPU ECU Memory (GiB) Instance Storage (GB) Linux/Unix Usage

Compute Optimized – Current generation

c4.large 2 8 3.75 EBS Only $0.116Number of instances 20 15 10 5 3 2 1

time(hr) 5.2 6.6 8.4 15.6 24.9 36.9 72.0Cost($) 13.92 12.18 10.44 9.28 8.7 8.584 8.468

Future Work

• Run additional tests on larger data sets• Complete benchmarking for more instance types• Incorporate t2 instances into network

Acknowledgements

• Pate Group (UVa)• Maria Phillips• Ian Finneran• Dr. Nathan Seifert (UVa)• Dr. Steve Shipman• Noah Anderson

This thesis was made possible through the work of: