Massive computation of singular values of small matrices on GPUs

This paper presents a fast and robust approach to evaluate the singular values of a very large number of small matrices on GPUs. The timings and the accuracy obtained are compared to those achieved by "state-of-the-art" libraries. The results show that, by suitably tuning the trade-off between computational speed and accuracy, a reasonable speedup over a fast multi-core CPU is possible.