SCHEDULE: NOV 15-20, 2015

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High Performance Model Based Image Reconstruction

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, ACM Student Research Competition Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Xiao Wang

ROOM:Level 4 - Lobby

ABSTRACT:

In Computed Tomography (CT) methods, Model Based Iterative Reconstruction (MBIR) produces higher quality images than commonly used Filtered Backprojection (FBP) but at a very high computational cost. We describe a new MBIR implementation, PSV-ICD, which significantly reduces the computational cost of MBIR while retaining its benefits. It describes a novel organization of the scanner data into super-voxels (SV) that, combined with a super-voxel buffer (SVB), dramatically increases locality and prefetching while enabling parallelism across SVs. Experimental data is presented showing an average speedup of 187X on 20 cores.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Xiao Wang - Purdue University

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