Aborescence:
f27ea5443b
11.0
12.0
12.1
12.2
13.0
13.1
13.37
14.0
14.1
14.2
15.0
bedlam
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user/anddt/system/hplip-plugin
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user/anddt/system/testdisk
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fourtysixandtwo
218fde6720
academic/spqr: Change i486 to i586
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il y a 2 ans | |
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| .. | ||
| patches | e04b7b18ba academic/spqr: Updated for SuiteSparse 5.8.1. | il y a 3 ans |
| README | 4e008c23b9 academic/spqr: Wrap README at 72 columns. | il y a 2 ans |
| slack-desc | 0683726349 academic/spqr: Fix slack-desc. | il y a 7 ans |
| spqr.SlackBuild | 218fde6720 academic/spqr: Change i486 to i586 | il y a 2 ans |
| spqr.info | e04b7b18ba academic/spqr: Updated for SuiteSparse 5.8.1. | il y a 3 ans |
README
SuiteSparseQR is an implementation of the multifrontal sparse QR
factorization method. Parallelism is exploited both in the BLAS and
across different frontal matrices using Intel's Threading Building
Blocks, a shared-memory programming model for modern multicore
architectures. It can obtain a substantial fraction of the
theoretical peak performance of a multicore computer.
This package is part of SuiteSparse.
This requires a BLAS/LAPACK implementation. Choose one of these package
sets:
* OpenBLAS (includes both a BLAS and a LAPACK implementation)
* atlas (includes both a BLAS and a LAPACK implementation)
* blas, lapack (the Netlib reference implementations)
If more than one set is installed (assuming there are no packaging
conflicts) then the auto-detection will use the first implementation
from this list that it finds. If in doubt, choose the Netlib reference
implementations; other packages that require a BLAS or LAPACK
implementation may not build if they are not configured to detect/use
alternate implementations.
factorization method. Parallelism is exploited both in the BLAS and
across different frontal matrices using Intel's Threading Building
Blocks, a shared-memory programming model for modern multicore
architectures. It can obtain a substantial fraction of the
theoretical peak performance of a multicore computer.
This package is part of SuiteSparse.
This requires a BLAS/LAPACK implementation. Choose one of these package
sets:
* OpenBLAS (includes both a BLAS and a LAPACK implementation)
* atlas (includes both a BLAS and a LAPACK implementation)
* blas, lapack (the Netlib reference implementations)
If more than one set is installed (assuming there are no packaging
conflicts) then the auto-detection will use the first implementation
from this list that it finds. If in doubt, choose the Netlib reference
implementations; other packages that require a BLAS or LAPACK
implementation may not build if they are not configured to detect/use
alternate implementations.