کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6906041 | 1447049 | 2018 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-GPU maximum entropy image synthesis for radio astronomy
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Multi-GPU maximum entropy image synthesis for radio astronomy Multi-GPU maximum entropy image synthesis for radio astronomy](/preview/png/6906041.png)
چکیده انگلیسی
The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly user dependent. Nevertheless, MEM has the following advantages: it is unsupervised, it has a statistical basis, it has a better resolution and better image quality under certain conditions. This work presents a high performance GPU version of non-gridding MEM, which is tested using real and simulated data. We propose a single-GPU and a multi-GPU implementation for single and multi-spectral data, respectively. We also make use of the Peer-to-Peer and Unified Virtual Addressing features of newer GPUs which allows to exploit transparently and efficiently multiple GPUs. Several ALMA data sets are used to demonstrate the effectiveness in imaging and to evaluate GPU performance. The results show that a speedup from 1000 to 5000 times faster than a sequential version can be achieved, depending on data and image size. This allows to reconstruct the HD142527 CO(6-5) short baseline data set in 2.1Â min, instead of 2.5 days that takes a sequential version on CPU.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Astronomy and Computing - Volume 22, January 2018, Pages 16-27
Journal: Astronomy and Computing - Volume 22, January 2018, Pages 16-27
نویسندگان
M. Cárcamo, P.E. Román, S. Casassus, V. Moral, F.R. Rannou,