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.
This adds third-party performance tests to use in comparing
Boost.Compute with other parallel/GPGPU frameworks like Intel's
TBB and NVIDIA's Thrust along with the C++ STL.
Also refactors the timing and profiling infrastructure and adds
a simple perf.py driver script for running performance tests.
This changes the vector<T> constructors which copy or initialize
data to take a queue argument used for performing the operations.
Previously they just took a context argument used to initialize the
buffer and then created a new command queue to use. This improves
performance by not requiring a new command queue and also fixes issues
when performing operations on a different command queue while the
vector was still being initialized.
This uses Boost.Preprocessor macros to allow zip iterators to work with
arbitrary number of elements (the current limit is maximum boost::tuple
size which is 10 by default).
Refs #50
This makes online cache use sha1 of the program source as key.
Introduces boost::compute::detail::sha1() function, which is moved
from compute::program into its own header file.
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.
Instead of building the program from source with the added comment
block (used for distinction between different platforms and devices
when offline cache is in use), only use the altered source for the
hash computation. This way users will not get unexpected results from
program.source().
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 improved reduce() algorithm implementation for
GPUs. Also adds checks to accumulate() which allow it to
use the higher-performance reduce() algorithm if possible.
