1. University of California, San Diego Structural Engineering SAN DIEGO SUPERCOMPUTER CENTER University of Zürich, Switzerland Image Guided Therapy Program Brigham and Women’s Hospital, Harvard Medical School PROBLEM: Neuro-surgeons seek to remove as much tumor tissue as possible while minimizing removal of healthy brain tissue Brain deforms during surgery Surgeons must align preoperative brain image with intra-operative images to provide surgeons the best opportunity for intra- surgical navigation A Novel Grid Architecture Integrating Real-Time Data and Intervention During Image Guided Therapy Radiologists and neurosurgeons at Brigham and Women’s Hospital, Harvard Medical School transfer 30/40 MB brain images (generated during surgery) to SDSC and other HPC centers for simulation using the MCP scheduler Parallel Finite element simulation of biomechanical model for volumetric deformation performed on HPC machine; output results are sent to BWH where updated images are shown to surgeons during surgery Transmission repeated every hour during 6-8 hour surgery Transmission and FEM simulation must take on the order of minutes Scheduling and On- demand Computing : MCP scheduler submits the same job to multiple machines MCP scheduler submits the same job to multiple machines As soon as one job starts MCP kills redundant jobs As soon as one job starts MCP kills redundant jobs Data transfer : Globus-url-copy and SRB NSF-ITR Grant NSF-ITR Grant 0427183 – SDSC, UCSD K. Baldridge, A. Majumdar, D. Choi, A. Birnbaum (SDSC), Petr Krysl (UCSD), A. Trivedi (gradstudent) NSF-ITR Grant 0426558 – Brigham and Women’s Hospital, Harvard S. K. Warfield, R. Kikinis, N. Archip (postdoc), S. Haker, neurosurgeons, radiologists Data transfer : Globus-url-copy and SRB Timing Results of Current Parallel Finite Element Code - 10.00 20.00 30.00 40.00 50.00 60.00 12481632 # of CPUs Time (sec) IBM Power3 Itanium2 TeraGrid IBM Power4 Brain shift

2. University of California, San Diego Structural Engineering SAN DIEGO SUPERCOMPUTER CENTER University of Zürich, Switzerland Image Guided Therapy Program Brigham and Women’s Hospital, Harvard Medical School Famuls FEM AMR deformation simulation using elastic solver; additional tetra-hedra, reducing error, in the interior Fusion of pre-op fMRI (green, red, yellow), pre-op MRI, and intra-op MRI; tumor is dark round region at the lower right bottom On-demand resource: Experiment on SDSC and NCSA TG cluster over 3 day period for request of 5 mins time from 2 to 64 CPUs. Job was terminated if it didn’t start in10 mins and next request processed. Total of 600 jobs submitted; ~50 for each bar on the plots. Results I: both clusters show decreasing likeli- hood of success with increasing # of requests. Results II: relationship between the size of request and the length of queue delay Additions to the ITR project Additions to the ITR project Initial small funding from IBM (I3) – innovation awardInitial small funding from IBM (I3) – innovation award Grad student summer intern ( Prf. D. Gannon, Indiana U.)Grad student summer intern ( Prf. D. Gannon, Indiana U.) Undergrad from Berkeley – REU summer scholarshipUndergrad from Berkeley – REU summer scholarship Multiple talks, SC demos, presentation, interest from other groups Multiple talks, SC demos, presentation, interest from other groups Parallel FEM roadmap Viscoelastic, viscoplastic: constitutive equations Viscoelastic, viscoplastic: constitutive equations Implement parallel sparse solver; domain decomposition of Famuls FEM code Implement parallel sparse solver; domain decomposition of Famuls FEM code Accuracy at the MRI voxel level – orders of magnitude increase in data, compute, networkAccuracy at the MRI voxel level – orders of magnitude increase in data, compute, network Dynamic multiscale image update Dynamic multiscale image update Grid Infrastructure roadmap Software to experiment with queue wait time, data transfer, network - flooding versus selective approach Software to experiment with queue wait time, data transfer, network - flooding versus selective approach security (patient privacy, encoding), data (meta-data, archive), visualization security (patient privacy, encoding), data (meta-data, archive), visualization NMI workflow integration NMI workflow integration ITRDDDAS Major cyberinfrastructure research: 100s of ORs and 10s of TFLOP centers Progress Todate and Future Research Direction