fMRI image registration with AFNI's 3dQwarp

Presenter(s): Junqi Yin (NICS)

Principal Investigator(s): Frank Skidmore (University of Alabama Birmingham)

The Analysis of Functional Neuroimaging (AFNI) software package is widely used in the community for the brain MR image analysis. For many types of analysis workflows, one important step is to register a subject's image to a pre-defined template so different subjects can be compared within a normalized coordination system. This is specially challenging if the subject has brain atrophy due to some kinds of neurological condition such as Parkinson's disease. The 3dQwarp code in AFNI is a non-linear image registration procedure that overcomes the drawbacks of a linear affine transformation. However, the existing OpenMP instrumentation in 3dQwarp is not efficient for small-patch optimization, and the lack of convergence criteria of the iterative algorithm also hurts the accuracy. Based on the profiling and benchmark, we have been working on the optimization of its OpenMP structure and the improvement of warped image fidelity, which can be used for voxel-to-voxel type of downstream analysis.

ECSS-er Junqi Yin (NICS) will be sharing observations from his work with PI Frank Skidmore (U Alabamba Birmingham) on Blacklight and Greenfield to optimize a widely used neuroimaging package called Analysis of Funtional Neuroimaging (AFNI).

Boosting molecular dynamics with advanced hardware and algorithms

Presenter(s): Lei Huang (TACC)

Principal Investigator(s): Dr. Doraiswami Ramkrishna (Purdue)

Presentation Slides

There are several open-sourced packages available for general purpose molecular dynamics (MD) simulations. However, researchers still need to develop their own MD engines under special circumstance. Dr. Doraiswami Ramkrishna's group at Purdue developed a package for umbrella sampling and molecular dynamics for polymorph prediction. By leveraging the power of Intel Xeon Phi and adopting several advanced algorithms in molecular dynamics, we achieved ~9x speedup and got a performance superior to LAMMPS.

Lei Huang (TACC) will tell us about his work with PI Doraiswami Ramkrishna (Purdue) to port several advanced algorithms in molecular dynamics to the Xeon Phi on Stampede with a factor of 9 speedup.