کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8067235 | 1521083 | 2018 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms
ترجمه فارسی عنوان
چند کاره مونت کارلو در پردازنده های گرافیکی: مقایسه الگوریتم های مبتنی بر رویداد و تاریخ
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
چکیده انگلیسی
This paper presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20-40â¯CPU cores on the K40 GPU and 60-80â¯CPU cores on the P100 GPU is achieved. In addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Annals of Nuclear Energy - Volume 113, March 2018, Pages 506-518
Journal: Annals of Nuclear Energy - Volume 113, March 2018, Pages 506-518
نویسندگان
Steven P. Hamilton, Stuart R. Slattery, Thomas M. Evans,