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GSOC 2017 PROJECT

Implement GeneMANIA in Julia for High-performance Computing

The aim of the project is to Implement GeneMANIA in Julia to optimize netDx for high-performance computing. The current Java-based implementation of...

Contributor
Guodong Xu
Mentors
Gary Bader, Shraddha Pai
Organization
National Resource for Network Biology (NRNB)Science and medicine
Program
GSoC 2017Completed

About this project

Description from the program archive

<p>The aim of the project is to Implement GeneMANIA in Julia to optimize netDx for high-performance computing.</p> <p>The current Java-based implementation of GeneMANIA scales poorly on compute clusters because of the interaction Java's memory management with the architecture of these systems. Removing this bottleneck would allow netDx to handle datasets on the order of 10K-100K patients, 100-1000X larger than the size of current datasets.</p> <p>Julia is a high-level programming language, with syntax similar to Matlab and Python. It provides efficient matrix representation and built-in parallel execution capabilities, making it better suited for high-performance computing (HPC). In addition to optimizing netDx for HPC, the network integration algorithm will be tuned for problems specific to netDx, such as having relatively fewer nodes and more networks.</p>

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Data: Google Summer of Code public archive. This project in the official archive