Multifrontral multithreaded rank-revealing sparse QR factorization
Multifrontral multithreaded rank-revealing sparse QR factorization
复制标题
多前沿多线程秩揭示稀疏 QR 分解
DOI：
--
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
T. Davis
中科院分区：
文献类型：
--
作者：
T. Davis
SuiteSparseQR is a sparse multifrontal QR factorization algorithm.
Dense matrix methods within each frontal matrix enable
the method to obtain high performance on multicore architectures. Parallelism
across different frontal matrices is handled with Intel's Threading Building
Blocks library.
Rank-detection is performed within each
frontal matrix using Heath's method, which does not require column pivoting.
The resulting sparse QR factorization obtains a substantial fraction of the
theoretical peak performance of a multicore computer.
