کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4977925 | 1452106 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Conjugate gradient method with graphics processing unit acceleration: CUDA vs OpenCL
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Performance computations depend on the machine architecture, the operating system, the problem studied and obviously on the programming implementation. Solving partial differential equations by numerical methods such as the finite element method requires the solution of large sparse linear systems. Graphics processing unit (GPU) is now commonly used to accelerate numerical simulations and most supercomputers provide large number of GPUs to their users. This paper proposes a comparison of both CUDA and OpenCL GPU languages to take the highest performance of multi-GPUs clusters. We analyse, evaluate and compare their respective performances for computing linear algebra operations and for solving large sparse linear systems with the conjugate gradient iterative method on multi-GPUs clusters.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 111, September 2017, Pages 32-42
Journal: Advances in Engineering Software - Volume 111, September 2017, Pages 32-42
نویسندگان
Abal-Kassim Cheik Ahamed, Frédéric Magoulès,