کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
461439 696598 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Surfing the optimization space of a multiple-GPU parallel implementation of a X-ray tomography reconstruction algorithm
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
Surfing the optimization space of a multiple-GPU parallel implementation of a X-ray tomography reconstruction algorithm
چکیده انگلیسی

The increasing popularity of massively parallel architectures based on accelerators have opened up the possibility of significantly improving the performance of X-ray computed tomography (CT) applications towards achieving real-time imaging. However, achieving this goal is a challenging process, as most CT applications have not been designed for exploiting the amount of parallelism existing in these architectures. In this paper we present the massively parallel implementation and optimization of Mangoose++, a CT application for reconstructing 3D volumes from 2D images collected by scanners based on cone-beam geometry. The main contribution of this paper are the following. First, we develop a modular application design that allows to exploit the functional parallelism inside the application and to facilitate the parallelization of individual application phases. Second, we identify a set of optimizations that can be applied individually and in combination for optimally deploying the application on a massively parallel multi-GPU system. Third, we present a study of surfing the optimization space of the modularized application and demonstrate that a significant benefit can be obtained from employing the adequate combination of application optimizations.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems and Software - Volume 95, September 2014, Pages 166–175
نویسندگان
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