LDRD final report : autotuning for scalable linear algebra.

Heroux, Michael Allen ; Marker, Bryan (University of Texas at Austin, Austin, TX)

关键词: ALGEBRA;    KERNELS;    PERFORMANCE;    TUNING;   

DOI  :  10.2172/1029773
RP-ID  :  SAND2011-7049
PID  :  OSTI ID: 1029773
Others  :  TRN: US201201%%183

学科分类：社会科学、人文和艺术（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

This report summarizes the progress made as part of a one year lab-directed research and development (LDRD) project to fund the research efforts of Bryan Marker at the University of Texas at Austin. The goal of the project was to develop new techniques for automatically tuning the performance of dense linear algebra kernels. These kernels often represent the majority of computational time in an application. The primary outcome from this work is a demonstration of the value of model driven engineering as an approach to accurately predict and study performance trade-offs for dense linear algebra computations.