کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6915877 | 862924 | 2016 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimising the performance of the spectral/hp element method with collective linear algebra operations
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Optimising the performance of the spectral/hp element method with collective linear algebra operations Optimising the performance of the spectral/hp element method with collective linear algebra operations](/preview/png/6915877.png)
چکیده انگلیسی
As computing hardware evolves, increasing core counts mean that memory bandwidth is becoming the deciding factor in attaining peak performance of numerical methods. High-order finite element methods, such as those implemented in the spectral/hp framework Nektar++, are particularly well-suited to this environment. Unlike low-order methods that typically utilise sparse storage, matrices representing high-order operators have greater density and richer structure. In this paper, we show how these qualities can be exploited to increase runtime performance on nodes that comprise a typical high-performance computing system, by amalgamating the action of key operators on multiple elements into a single, memory-efficient block. We investigate different strategies for achieving optimal performance across a range of polynomial orders and element types. As these strategies all depend on external factors such as BLAS implementation and the geometry of interest, we present a technique for automatically selecting the most efficient strategy at runtime.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 310, 1 October 2016, Pages 628-645
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 310, 1 October 2016, Pages 628-645
نویسندگان
D. Moxey, C.D. Cantwell, R.M. Kirby, S.J. Sherwin,