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A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor Je’aime Powell

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Abstract The Polar Grid team was tasked with testing the VikeGrid system to ensure it was ready for grid computing. This was achieved by installing the Condor client on the iMac computers located in Dixon hall, Lane hall, and E.V Wilkins on the campus of Elizabeth City State University. Condor allowed jobs to be submitted to VikeGrid and distributed to one or more nodes. The job that the team submitted to Condor was the compiled Sieve of Eratosthenes C++ code. This code generated prime numbers between 0 to 500,000 and was essential in testing the job submission process. The compiled code that was used in the script file was submitted to VikeGrid through Condor. These jobs were then distributed to available nodes for processing. After each successful job submission, log files were created to record statistical data of the elapsed time it took to process its entire submission along with the time it took to process each individual job. The data from these tables were imported to Mini Tab, which is statistical analysis software. An analysis of variance was then performed to determine if the elapsed time of the submissions varied within a 5 percent level of significance. From that a determination of if increasing the number of nodes decreased the elapsed time thereby showing a performance increase.

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Page 1: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid

Team MembersJerNettie BurneyRobyn EvansMichael Austin

MentorJe’aime Powell

Page 2: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Nature and Background of the Study

Page 3: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

AbstractThe Polar Grid team was tasked with testing the VikeGrid system to ensure it was

ready for grid computing. This was achieved by installing the Condor 7.4.0 client on the iMac computers located in Dixon hall, Lane hall, and E.V Wilkins on the campus of Elizabeth City State University. Condor allowed jobs to be submitted to VikeGrid and distributed to one or more nodes. The job that the team submitted to Condor was the compiled Sieve of Eratosthenes C++ code. This code generated prime numbers between 0 to 500,000 and was essential in testing the job submission process. The compiled code that was used in the script file was submitted to VikeGrid through Condor. These jobs were then distributed to available nodes for processing.

After each successful job submission, log files were created to record statistical data of the elapsed time it took to process its entire submission along with the time it took to process each individual job. The data from these tables were imported to Mini Tab, which is statistical analysis software. An analysis of variance was then performed to determine if the elapsed time of the submissions varied within a 5 percent level of significance. From that a determination of if increasing the number of nodes decreased the elapsed time thereby showing a performance increase.

Page 4: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Background of the Problem•The Polar Grid team’s ultimate goal was

to find a Titanic prime. •Finding a prime number generator•Test the grid

Page 5: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Key Terms• Cluster• Grid• Script• Condor

• Node• VikeGrid• Kitoto • ANOVA

Page 6: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Hypothesis •The team hypothesized that the elapsed

time for a single node to complete a submitted job would take much longer than multiple nodes collaborating to complete the same job.

Page 7: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Methodology

Page 8: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Definition of the Population

Page 9: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Log files

Page 10: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Definition of Population

Page 11: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Research Design•Defined the problem•Analyzed a solution•Performed experiment •Analyzed results

Page 12: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Analysis of Data

Page 13: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Visual Representation of Data

Page 14: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Visual Representation of Data

Page 15: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Visual Representation of Data

1 2 4 8 16 24 36 460:00:00

1:12:00

2:24:00

3:36:00

4:48:00

6:00:00

Elapsed Time

Number of Nodes

Tim

e in

Hou

rs:M

inut

es:S

econ

ds

Page 16: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Summary, Conclusions, and Recommendations

Page 17: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Conclusions based off Statistical Analysis of the Data

One-way ANOVA: Number of Workers, Elapsed Time

Source DF SS MS F PFactor 1 1165 1165 8.22 0.012Error 14 1983 142Total 15 3148

S = 11.90 R-Sq = 37.01% R-Sq(adj) = 32.51%

Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev ---------+---------+---------+---------+Number of Workers 8 17.13 16.83 (--------*--------)Elapsed Time 8 0.06 0.07 (--------*--------) ---------+---------+---------+---------+ 0 10 20 30

Pooled StDev = 11.90

Page 18: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Challenges•VikeGrid incomplete•Perl Script

▫Errors were made while installing condor•Sbin

▫Sbin paths were not included•Xcode

▫Updates required•Source code•Submission of scripts

Page 19: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Acknowledgements•Michael Jefferson

▫For his assistance in correcting the code in Visual Studio.

•Dr. Eric Akers▫For his assistance in modifying the code to

make primes between 0 to 500000 and help with the output of the code.

Page 20: A Comparison of Job Duration Utilizing High Performance Computing on a Distributed Grid Team Members JerNettie Burney Robyn Evans Michael Austin Mentor

Future works•Titanic Prime Numbers•Multiple job submission •Test on both Linux and Windows