Computational Anatomy: Utilizing BIRN and TeraGrid Infrastructure. Anthony Kolasny Johns Hopkins University. Center for Imaging Science. Institute for Computational Medicine. Computational Anatomy.
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Computational Anatomy: Utilizing BIRN and TeraGrid Infrastructure
Johns Hopkins University
Institute for Computational Medicine
D'Arcy believed that biologists of his day over emphasized the role of evolution, and under emphasized the roles of physical laws and mechanics, as determinants of the form and structure of living organisms.
Image from D'arcy Thompson "On Growth and Form"
"Computational anatomy: an emerging discipline," Ulf Grenander
and Michael I. Miller (Quart. Appl. Math. 56: 617-94, December 1998)
Large Deformation Diffeomorphic Metric Mapping
a metric or distance function is a function which defines a distance
between elements of a set.
Multidimensional Scaling (MDS)
Metric multidimensional scalinng (MDS)
A superset of classical MDS that generalizes the optimization procedure to a variety of loss functions and input matrices of known distances with weights and so on.
Linear discriminant analysis (LDA)
Used in statistics to find the linear combination of features which best separate two or more classes of object or event.
Biomedical Informatics Research Network (BIRN)
BIRN is a National Center for Research Resources (NCRR) initiative aimed at creating a testbed to address biomedical researchers
Shape Analysis - A Morphometry BIRN Project
of Segmented Structures
Goal: comparison and quantification of structures’ shape and volumetric differences across patient populations
Identifying Shape Analysis Requirements
Leverage BIRN SRB Storage
BIRN + TeraGrid would write to a common area
Port LDDMM to utilize TeraGrid
Work with Intel to optimize code. (30% speedup)
Provide a portal interface to LDDMM
Allow other people access to the program
Utilize VTK for visualization
Utilize Wikis for documentation
Leveraging the BIRN Infrastructure
First & Second Iteration of Shape Analysis Project
Classification (45 Train only)
Preparing for the 101 Data Set
Classification (45 Train + 56 Test)
* : mean(1,•)
* : mean(2,3,▲)
56 Test points
0.0042 ± 0.001
Publications: M. Miller, C. Priebe, B. Fischl, A. Kolasny, Y. Park, E. Busa, J. Jovivich, P. Yu, B. Dickerson, R. Buckner, Morphometry BIRN , Collaborative Computational Anatomy:The Perfect Storm for MRI Morphometric Study of the Human Brain via Diffeomorphic Metric Mapping, Multidimensional Scaling and Linear Disriminant Analysis, Proceedings of the National Academy of Sciences - Submitted for review
Secure Shell FileSystem (SSHFS)
a file system for Linux (and other operating systems with a FUSE implementation, such as Mac OS X) capable of operating on files on a remote computer using just a secure shell login on the remote computer. On the local computer where the SSHFS is mounted, the implementation makes use of the FUSE (Filesystem in Userspace) kernel module. The practical effect of this is that the end user can seamlessly interact with remote files being securely served over SSH just as if they were local files on his/her computer.
The current implementation of SSHFS using FUSE is a rewrite of an earlier version. The rewrite was done by Miklos Szeredi, who also wrote FUSE.
sshfs [email protected]:/path/to/remote_dir local_mountpoint
Autofs and SSHFS
Autofs allows automatic mounting of remote sshfs filesytems. CIS users may access remote data as local directories. Common local directory structure allows for more effective scripting and analysis of data.
Gluing Clusters and Storage with SSHFS
Utilizing samba and smbwebclient, we were able create a web interface to clustered data.
Common Data Namespace Improved Throughput
/gpfs-wan is shared at SDSC and NCSA in a common location. Using sshfs, /gpfs-wan was mounted on BIRN SDSC Cluster and the BIRN JHU cluster adding more processing power.
Monitoring the Queues
Monitoring the SDSC, NCSA, JHU and BIRN clusters is as simple as reading
email. Monitoring what's left to run is as easy as 'cd run; ls | wc'.
Wikis are extremely helpful in keeping track of projects and monitor progress
Utilizing Paraview we are able to
visualize structures and velocity data.
BIRN LDDMM Portal
$300K - $40K = Saved $260K in storage costs.
Invested $70k in development cluster. Current cumulative TeraGrid time 640K cpu/hrs.
TeraGrid help desk an extremely valuable asset.
2002.09 - BIRN All Hands
2002.10 - Supercomputing Baltimore emerging TeraGrid
2003.02 - Morph BIRN - define SASHA project
2003.05 - BIRN Rack installed
2003.08 - lddmm writes vtk output
2003.09 - Installed itanium2 cluster
2003.09 - lddmm processing on IBM SP (18 subjects)
2003.10 - BIRN All Hands – Shape Analysis Pipeline (not conclusive from 18 subjects)
2004.02 - Morph BIRN All Hands
2004.02 - 40K cpu/hrs award 45x45 processing used SRB
2004.06 - Human Brain Mapping - Emerging Classifier
2004.08 - Intel HPC workshop 30% performance improvement
2005.09 - 300K cpu/hrs award
2006.01 - Started processing 101x101 processing using GPFS-WAN
2006.06 - Human Brain Mapping Conference – Present lddmm, MDS, LDA
2006.09 - Submitted PNAS paper
2006.10 - SDSC Calendar highlights BIRN Shape Analysis Project
2006.09 - 300K cpu/hrs other lddmm projects Mouse BIRN, OASIS, VETSA, ADNI
Michael I. Miller