%0 Conference Paper %B 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing %D 2015 %T GPU-accelerated Co-design of Induced Dimension Reduction: Algorithmic Fusion and Kernel Overlap %A Hartwig Anzt %A Eduardo Ponce %A Gregory D. Peterson %A Jack Dongarra %X In this paper we present an optimized GPU co-design of the Induced Dimension Reduction (IDR) algorithm for solving linear systems. Starting from a baseline implementation based on the generic BLAS routines from the MAGMA software library, we apply optimizations that are based on kernel fusion and kernel overlap. Runtime experiments are used to investigate the benefit of the distinct optimization techniques for different variants of the IDR algorithm. A comparison to the reference implementation reveals that the interplay between them can succeed in cutting the overall runtime by up to about one third. %B 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing %I ACM %C Austin, TX %8 2015-11 %G eng