%0 Conference Paper %B 2015 SIAM Conference on Applied Linear Algebra %D 2015 %T Comparing Hybrid CPU-GPU and Native GPU-only Acceleration for Linear Algebra %A Mark Gates %A Stanimire Tomov %A Azzam Haidar %X Accelerating dense linear algebra using GPUs admits two models: hybrid CPU-GPU and GPU-only. The hybrid model factors the panel on the CPU while updating the trailing matrix on the GPU, concentrating the GPU on high-performance matrix multiplies. The GPU-only model performs the entire computation on the GPU, avoiding costly data transfers to the CPU. We compare these two approaches for three QR-based algorithms: QR factorization, rank revealing QR, and reduction to Hessenberg. %B 2015 SIAM Conference on Applied Linear Algebra %I SIAM %C Atlanta, GA %8 2015-10 %G eng