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.
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 removes the timer class. The technique of measuring the time
difference between two different OpenCL markers on a command queue
is not portable to all OpenCL implementations (only works on NVIDIA).
A new internal timer class has been added which uses boost::chrono
(or std::chrono if BOOST_COMPUTE_TIMER_USE_STD_CHRONO is defined).
This new timer is used by the benchmarks to measure time elapsed
on the host.
