The preparation of these files was supported by Schlumberger Palo Alto
Research, AT&T Bell Laboratories, and Morgan Kaufmann Publishers.
Shirley Jowell, of Morgan Kaufmann Publishers, and Peter F.
Patel-Schneider, of AT&T Bell Laboratories collaborated on their
preparation. These instructions can be modified and used in other conferences as long
as credit to the authors and supporting agencies is retained, this notice
is not changed, and further modification or reuse is not restricted.
Neither Shirley Jowell nor Peter F. Patel-Schneider can be listed as
contacts for providing assistance without their prior permission.
To use for other conferences, change references to files and the
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Image reconstruction is observed to be one of the most common problem because of it's large data movement and non-trivial data dependencies. In the past, these problems were tackled by many high performance hardware such as FPGA's and GPGPU's. This also reflects the investemts to be made in these supercomputers for real time reconstruction of clinical computed tomography (CT) applications. Medical imaging systems are employing high performance computing (HPC) technology to meet their time constraints. This paper presents different optimizations to the volume reconstruction and implement it on a commodity hardware such as x86 based multicore system. This paper chooses to perform its implementaion on Intel Xeon X5365 multicore processor. We perform different levels of parallelization and analyse each of them and report their results with respect to serial implementation. The objective of this paper is to understand the constraints of volume reconstruction in multicore architecture and optimize them while preserving the quality of the reconstructed image.
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Facultad de Ingeniería, Universidad de Costa Rica