
CholeskyQR2 for Ill-conditioned Matrices (CholeskyQR2-IM) is a modern C++ library designed to compute the QR factorization of extremely ill-conditioned tall-and-skinny matrices. It is based on the Cholesky QR2 algorithm, which is widely recognized for its performance and ease of parallelization on distributed memory systems. The CholeskyQR2-IM presents an alternative approach that combines the traditional CholeskyQR2 with the shifting technique and the modified Gram-Schmidt process. The innovative approach improves both the numerical stability of the algorithm and the accuracy of the calculated factor Q. The library is specifically designed for QR factorization of large tall-and-skinny matrices on distributed memory systems and provides full support for both GPUs and modern CPUs.
HPC, QR factorization, Parallel processing, GPU, Linear algebra, CholeskyQR
HPC, QR factorization, Parallel processing, GPU, Linear algebra, CholeskyQR
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
