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All checksums have been double-checked against existing RMD160 and
SHA512 hashes
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Install the new interchangeable BLAS system created by Thomas Orgis,
currently supporting Netlib BLAS/LAPACK, OpenBLAS, cblas, lapacke, and
Apple's Accelerate.framework. This system allows the user to select any
BLAS implementation without modifying packages or using package options, by
setting PKGSRC_BLAS_TYPES in mk.conf. See mk/blas.buildlink3.mk for details.
This commit should not alter behavior of existing packages as the system
defaults to Netlib BLAS/LAPACK, which until now has been the only supported
implementation.
Details:
Add new mk/blas.buildlink3.mk for inclusion in dependent packages
Install compatible Netlib math/blas and math/lapack packages
Update math/blas and math/lapack MAINTAINER approved by adam@
OpenBLAS, cblas, and lapacke will follow in separate commits
Update direct dependents to use mk/blas.buildlink3.mk
Perform recursive revbump
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C++14 default language.
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Problems found locating distfiles:
Package dfftpack: missing distfile dfftpack-20001209.tar.gz
Package eispack: missing distfile eispack-20001130.tar.gz
Package fftpack: missing distfile fftpack-20001130.tar.gz
Package linpack: missing distfile linpack-20010510.tar.gz
Package minpack: missing distfile minpack-20001130.tar.gz
Package odepack: missing distfile odepack-20001130.tar.gz
Package py-networkx: missing distfile networkx-1.10.tar.gz
Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz
Package quadpack: missing distfile quadpack-20001130.tar.gz
Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden). All existing
SHA1 digests retained for now as an audit trail.
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Ipopt (Interior Point OPTimizer, pronounced eye-pea-Opt)
is a software package for large-scale nonlinear optimization.
It is designed to find (local) solutions of mathematical
optimization problems of the form
min_{x in R^n} f(x)
s.t. g_L <= g(x) <= g_U
x_L <= x <= x_U
where f(x): R^n --> R is the objective function,
and g(x): R^n --> R^m are the constraint functions.
The vectors g_L and g_U denote the lower and upper bounds on the
constraints, and the vectors x_L and x_U are the bounds on the
variables x. The functions f(x) and g(x) can be nonlinear and
nonconvex, but should be twice continuously differentiable.
Note that equality constraints can be formulated in the above
formulation by setting the corresponding components of g_L and
g_U to the same value.
Ipopt is part of the COIN-OR Initiative.
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