Automatic tuning to performance modelling of matrix polynomials on multicore and multi-GPU systems

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• 作者：Murilo Boratto ; Pedro Alonso ; Domingo Giménez…
• 关键词：Automatic tuning ; Matrix polynomials ; Performance ; Multicore ; Multi ; GPU
• 刊名：The Journal of Supercomputing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：73
• 期：1
• 页码：227-239
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Programming Languages, Compilers, Interpreters; Processor Architectures; Computer Science, general;
• 出版者：Springer US
• ISSN：1573-0484
• 卷排序：73

文摘

Automatic tuning methodologies have been used in the design of routines in recent years. The goal of these methodologies is to develop routines which automatically adapt to the conditions of the underlying computational system so that efficient executions are obtained independently of the end-user experience. This paper aims to explore programming routines that can automatically be adapted to the computational system conditions thanks to these automatic tuning methodologies. In particular, we have worked on the evaluation of matrix polynomials on multicore and multi-GPU systems as a target application. This application is very useful for the computation of matrix functions like the sine or cosine but, at the same time, the application is very time consuming since the basic computational kernel, which is the matrix multiplication, is carried out many times. The use of all available resources within a node in an easy and efficient way is crucial for the end user.