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

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.

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.

Student

Guodong Xu

Mentors

  • Gary Bader
  • Shraddha Pai
close

2017