ツリー:
9303d7f91a
11.0
12.0
12.1
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14.0
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15.0
bedlam
bedlam-name-fixes
dive
erik
gitignore
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master
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python-renames
rworkman
urchlay
user/aclemons/updates
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user/anddt/development/glm
user/anddt/development/gnustep-base
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user/anddt/libraries/girara
user/anddt/libraries/goffice
user/anddt/libraries/gtksourceview4
user/anddt/libraries/imlib2
user/anddt/libraries/jsoncpp
user/anddt/libraries/libnova
user/anddt/libraries/libopenmpt
user/anddt/libraries/libtorrent
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user/anddt/misc/discount
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user/anddt/network/putty
user/anddt/network/rclone
user/anddt/network/rtorrent
user/anddt/network/sshguard
user/anddt/network/strongswan
user/anddt/network/umurmur
user/anddt/network/yt-dlp
user/anddt/network/znc
user/anddt/office/gnumeric
user/anddt/office/sigil
user/anddt/system/FontAwesome
user/anddt/system/conky
user/anddt/system/fakeroot
user/anddt/system/hplip-plugin
user/anddt/system/postgresql
user/anddt/system/testdisk
user/anddt/system/worker
user/anddt/system/xen
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user/chris.willing/updates
user/dslackw/updates
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user/kingbeowulf/updates
user/mario/updates
user/ponce/updates
user/pprkut/updates
willysr
wxWidgets-wip
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B. Watson
4e008c23b9
academic/spqr: Wrap README at 72 columns.
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2 年 前 | |
|---|---|---|
| .. | ||
| patches | e04b7b18ba academic/spqr: Updated for SuiteSparse 5.8.1. | 3 年 前 |
| README | 4e008c23b9 academic/spqr: Wrap README at 72 columns. | 2 年 前 |
| slack-desc | 0683726349 academic/spqr: Fix slack-desc. | 8 年 前 |
| spqr.SlackBuild | 63daf9f79a All: Support $PRINT_PACKAGE_NAME env var | 3 年 前 |
| spqr.info | e04b7b18ba academic/spqr: Updated for SuiteSparse 5.8.1. | 3 年 前 |
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.