This adds a new macro which allows the user to adapt a C++ struct
or class for use with OpenCL given its type, name, and members.
This allows for custom user-defined data-types to be used with the
Boost.Compute containers and algorithms.
This adds an experimental directory which contains various
experimental algorithms and functions. The files and APIs
under this directory are experimental and unstable.
detail::getenv() function was not declared inline, which led to
`multiple definition` errors at link time when a program consisted of
multiple objects that included Boost.Compute headers.
Fixed the problem and added core.multiple_objects test.
This adds interoperability support between Boost.Compute and various
other C/C++ libraries (Eigen, OpenCV, OpenGL, Qt and VTK). This eases
development for users using external libraries with Boost.Compute.
See kylelutz/compute#21
This adds program::build_with_source() function that both creates and
builds the program for the given context with supplied source and
compile options. In case BOOST_COMPUTE_USE_OFFLINE_CACHE macro is
defined, it also saves the compiled program binary for reuse in the
offline cache located in $HOME/.boost_compute folder on UNIX-like
systems and in %APPDATA%/boost_compute folder on Windows.
All internal uses of program::create_with_source() followed by
program::build() are replaced with program::build_with_source().
This adds a new macro to ease the definition of custom user
functions. The BOOST_COMPUTE_FUNCTION() macro creates a new
boost::compute::function<> object with the provided return
type, argument types, function name and OpenCL source code.
This adds a new unpack() function adaptor which converts
a function with N arguments to a function which takes a
single tuple argument with N components.
This is useful for calling built-in functions with the tuples
values returned from zip_iterator. This also removes the now
un-needed binary_transform_iterator.
This adds a program cache which can be used by algorithms and other
functions to store programs which may be re-used. This improves
performance by reducing the need for costly recompilation of commonly
used programs.
Program caches are context specific and multiple copies of the same
context will use the same program cache. They are created and accessed
by the global get_program_cache() function.
For now, only a few algorithms and functions (radix sort, mersenne
twister, fixed size sorts) make use of the program cache.
This adds a sort_by_transform() algorithm which sorts a sets of
values based on the value of a transform function.
For example, this can be used to sort a set of vectors by their
length (when used with the length<T>() function) or by a single
component (when used with the get<N>() function).
This adds a new sort_by_key() algorithm which sorts a range
of values by a range of keys with a comparison operator.
For now this is only implemented by the serial insertion sort
algorithm. In the future it will be ported to the other sorting
algorithms (e.g. radix sort).
This adds a random number distribution which generates random
numbers in a uniform distribution.
Also adds a convenience algorithm which fills a range with
uniformly distributed random numbers between two values.
This adds a simple inplace_merge() algorithm which merges
two contiguous sorted ranges in-place.
For now, the implementation simply copies the ranges to
two temporary vectors and calls merge().
This adds support for using the get<N>() function in lambda
expressions to extract a single component of an aggregate type.
Also adds a test of using boost::tuple<> to store a user-defined
data type on the device and sort them by their first component
using a lambda expression as the comparator.
This adds a get<N>() function which returns the n'th element
of an aggregate type (e.g. vector type, pair, tuple).
This unifies the functionality of, and replaces, the get_pair()
and vector_component() functions.
This adds a clamp_range() algorithm which clamps a range
of values between a low and high value. This is based on
the algorithm of the same name in Boost.Algorithm.
This implements the merge() algorithm which merges two
ranges of sorted values into a single sorted range.
The current implementation uses a simple serial merge
algorithm. A GPU optimized version is coming soon.
