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Team Name

Reetu and Friends

 

Team Members

Reetu Tuteja - Created the Sequenceserver2.0 app on Discovery Environment

Jennen Maryniak - presentation

Jiatian Wang - initial Makeflow and Work Queue scripts

Hayden Dunn

Erika Tapia - benchmarking and documentation

Andy Garcia

Nick Reppe

 

Project Summary:

An implementation of Discovery Environment using an app created via VICE in CyVerse. 


Project Description


Code Availability

https://github.com/KartinJulia/SequenceServer


Installing/Running Instructions

(Through Discovery Environment, open a SequenceServer app, upload a query through the input GUI on DE, run, and look at analysis.)?

 

Project Timeline/Plan


Benchmarking


Benchmarking was ran by running the sequenceserver app we created in the Discovery Environment (DE) within CyVerse. Before launching the app, the number of cores was specified in the drop-down field "Number of threads":




The running analysis was accessed which allowed us to paste the protein sequences in Sequence Server to run BLAST:





Conclusions: Sequence server ran on the same set of protein sequences and database on 1, 2, 4 and 8 cores. A significant decrease in run-time was observed as more cores were involved in running queries. Running queries on 8 cores clearly reduces run-time as compared to running queries on simply 1 core. 

 

Number of Protein Sequences

Time (seconds)

1 CORE

Time (seconds)

2 CORES

Time (seconds)

4 CORES

Time (seconds)

8 CORES

130.92.121.120.87
552.6127.5517.6422.34
1085.1139.6724.6729.59
50491.97264.41183.23237.03
100488.24374.11255.75321.87
5001171.71646.75935.87942.22

 

 

Presentation

https://docs.google.com/presentation/d/1D755s013X6MVVlTszQXayMuy0A3CpYIpEdLfHAsX_ig/edit?usp=sharing

https://www.loom.com/share/db109980b7954f0e81ae7b59fd9f8196

https://www.loom.com/share/fdcc53eeb53942d29577145851f8f0f9

 

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