LDRD final report : autotuning for scalable linear algebra.

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

Sandia National Laboratories

关键词: Algebra;    Tuning;    Performance;    Kernels;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;   

DOI  :  10.2172/1029773
RP-ID  :  SAND2011-7049
RP-ID  :  AC04-94AL85000
RP-ID  :  1029773

美国|英语

来源: UNT Digital Library

【 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.