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Accelerating Discovery [clear filter]
Thursday, July 21
 

10:30am EDT

AD: Computational Considerations in Transcriptome Assemblies and Their Evaluation, using High Quality Human RNA-Seq Data
It is crucial to understand the performance of transcriptome assemblies to improve current practices. Investigating the factors that affect a transcriptome assembly is very important and is the primary goal of our project. To that end, we designed a multi-step pipeline consisting of variety of pre-processing and quality control steps. XSEDE allocations enabled us to achieve the computational demands of the project. The high memory Blacklight and Greenfield systems at Pittsburgh Supercomputing Center were essential to accomplish multiple steps of this project. This paper presents the computational aspects of our comprehensive transcriptome assembly and validation study.


Thursday July 21, 2016 10:30am - 11:00am EDT
Chopin Ballroom

11:00am EDT

AD: Improving the Scalability of a Charge Detection Mass Spectrometry Workflow
The Indiana University (IU) Department of Chemistry’s Martin F. Jarrold (MFJ) Research Group studies a specialized technique of mass spectrometry called Charge Detection Mass Spectrometry (CDMS). The goal of mass spectrometry is to determine the mass of chemical and biological compounds, and with CDMS, the MFJ Research Group is extending the upper limit of mass detection. These researchers have developed a scientific application, which accurately analyzes raw CDMS data generated from their mass spectrometer. This paper explains the comprehensive process of optimizing the group’s workflow by improving both the latency and throughput of their CDMS application. These significant performance improvements enabled high efficiency and scalability across IU’s Advanced Cyberinfrastructure; overall, this analysis and development resulted in a 25x speedup of the application.


Thursday July 21, 2016 11:00am - 11:30am EDT
Chopin Ballroom

11:30am EDT

AD: Scaling GIS analysis tasks from the desktop to the cloud utilizing contemporary distributed computing and data management approaches: A case study of project-based learning and cyberinfrastructure concepts
In this paper we present the experience of scaling in parallel a geographic information system modeling framework to hundreds of processors. The project began in an active learning cyberinfrastructure course which was followed by an XSEDE ECSS effort in collaboration across multiple-institutions.


Thursday July 21, 2016 11:30am - 12:00pm EDT
Chopin Ballroom