Knowledge Discovery in Auto-tuning Parallel Numerical Library

Authors:
Hisayasu Kuroda;Takahiro Katagiri;Yasumasa Kanada
Affiliations:
-;-;-
Venue:
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Year:
2002

Citing 3
Cited 4

Optimizing matrix multiply using PHiPAC: a portable, high-performance, ANSI C coding methodology

ICS '97 Proceedings of the 11th international conference on Supercomputing
ScaLAPACK user's guide

ScaLAPACK user's guide
A fast Fourier transform compiler

Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation

Effect of auto-tuning with user's knowledge for numerical software

Proceedings of the 1st conference on Computing frontiers
ABCLib_DRSSED: A parallel eigensolver with an auto-tuning facility

Parallel Computing
ABCLibScript: a directive to support specification of an auto-tuning facility for numerical software

Parallel Computing
An evaluation towards automatically tuned eigensolvers

LSSC'05 Proceedings of the 5th international conference on Large-Scale Scientific Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes the parallel numerical library called ILIB which realises auto-tuning facilities with selectable calculation kernels, communication methods between processors, and various number of unrolling for loop expansion. This auto-tuning methodology has advantage not only in usability of library but also in performance of library. In fact, results of the performance evaluation show that the auto-tuning or auto-correction feature for the parameters is a crucial technique to attain high performance. A set of parameters which are auto-selected by this auto-tuning methodology gives us several kinds of important knowledge for highly efficient program production. These kinds of knowledge will help us to develop some other high-performance programs, in general.