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.
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 fixes a few issues encountered when using iterators with a
void value_type (e.g. std::insert_iterator<>).
The is_contiguous_iterator meta-function was refactored to always
return false for iterators with a void value_type and avoid
instantiating types for containers with a void value_type
(e.g. std::vector<void>::iterator) which previously resulted
in compilation errors.
This adds a system-wide default command queue. This queue is
accessible via the new static system::default_queue() method.
The default command queue is created for the default compute
device in the default context and is analogous to the default
stream in CUDA.
This changes how algorithms operate when invoked without an
explicit command queue. Previously, each algorithm had two
overloads, the first expected a command queue to be explicitly
passed and the second would create and use a temporary command
queue. Now, all algorithms take a command queue argument which
has a default value equal to system::default_queue().
This fixes a number of race-conditions and performance issues
througout the library associated with create, using, and
destroying many separate command queues.
This fixes a few memory handling issues between device_ptr,
buffer_iterator, buffer_value, allocator, and malloc/free.
Previously, memory buffers that were allocated by allocator and
malloc were being retained (via clRetainMemObject() in buffer's
constructor) by device_ptr, buffer_iterator and buffer_value.
Now, false is passed for the retain parameter to buffer's
constructor so that the buffer's reference count is not
incremented. Furthermore, the classes now set the buffer to
null before being destructed so that they will not decrement its
reference count (which normally occurs buffer's destructor).
The main effect of this change is that objects which refer to a
memory buffer but do not own it (e.g. device_ptr, buffer_iterator)
will not modify the reference count for the buffer. This fixes a
number of memory leaks which occured in longer running programs.
This adds a new scalar<T> "container" which stores a single
value in a memory buffer. This simplifies memory handling in
algorithms which read and write a single value.
This refactors the system::default_device() method. Now, the
default compute device for the system is only found once and
stored in a static variable. This eliminates many redundant
calls to clGetPlatformIDs() and clGetDeviceIDs().
Also, the default_cpu_device() and default_gpu_device() methods
have been removed and their usages replaced with default_device().
This fixes a couple of narrowing conversion warnings in the
device partitioning methods which were seen when compiling
VexCL with Boost.Compute in C++11 mode.
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 changes the vector class to not auto-initialize values
when it is created or resized. This improves performance by
eliminating a call to fill(). If needed, user code can call
fill() explicitly on the newly allocated values.
This increases the work-group size for the copy() kernel to be
up to 32 items based on the size of the input. This increases the
performance of copy() and related algorithms (e.g. transform()).
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 changes the enqueue_nd_range_kernel() method to return an
event object. This allows clients to monitor the progress of a
kernel executing on a device.
boost::compute::system::default_device() supports the following
environment variables:
BOOST_COMPUTE_DEFAULT_DEVICE for device name
BOOST_COMPUTE_DEFAULT_PLATFORM for OpenCL platform name
BOOST_COMPUTE_DEFAULT_VENDOR for device vendor name
If one or more of these variables is set, then device that satisfies
all conditions gets selected. If such a device is unavailable, then
the first available GPU is selected. If there are no GPUs in the
system, then the first available CPU is selected. Otherwise,
default_device() returns null device.
The hello_world example is modified to use default_device() instead
of default_gpu_device().
This adds a specialization of multiplies<T> for std::complex<T>
which implements complex number multiplication.
Also adds a simple test using transform() to verify the complex
multiplication works correctly.
This fixes an unused variable warning which occurs in the
get_base_iterator_buffer() function when the base iterator
is not a buffer iterator and thus the iter argument is not
used.
This fixes a bug in which boost::result_of() would return the
wrong result type for a function due to the new implementation
using decltype instead of the result_of protocol on compilers
that sufficently support C++11 (such as clang >= 3.2).
Now, boost::tr1_result_of() is used to explicitly request that
the result_of protocol be used even when decltype is supported
by the compiler.
This cleans up the constructor methods for the OpenCL wrapper
classes and unifies the API used for creating a wrapper class
object from the underlying OpenCL objects.
Now, every wrapper class has a constructor taking the OpenCL
object and an optional boolean retain parameter which indicates
whether the constructor should increment the reference count.
This updates the constructors for the image2d and image3d
classes to use the new clCreateImage() function instead of
the deprecated clCreateImage2D/3D() functions.
This changes the enqueue_marker() method in the command_queue
class to use clEnqueueMarkerWithWaitList() instead of the
deprecated clEnqueueMarker() function when compiling with
OpenCL 1.2.
This changes the enqueue_barrier() method in the command_queue
class to use clEnqueueBarrierWithWaitList() instead of the
deprecated clEnqueueBarrier() function when compiling with
OpenCL 1.2.
This remove the enqueue_wait_for_event() method from the
command_queue class as the clEnqueueWaitForEvents() function
has been deprecated in OpenCL 1.2.
This moves the unload_compiler() method from the system class
to the platform class. Also changes the method to use the
clUnloadPlatformCompiler() function instead of the deprecated
clUnloadCompiler() when compiling with OpenCL 1.2.
This moves the get_extension_function_address() method from
the system class to the platform class. Also changes the method
to use the clGetExtensionFunctionAddressForPlatform() function
instead of the deprecated clGetExtensionFunctionAddress() when
compiling with OpenCL 1.2.
This fixes a bug in the move-constuctor for the vector<T>
class.
Previously, the moved-from object was also deallocating the
memory buffer leading to an error when the moved-to object
attempted to use it. Now, the constructor checks if the buffer
is non-empty before deallocating it.
This removes support for cl_half (typedef'd to half_).
The issue is that the cl_half type is indistinguishable
from the cl_ushort type (both are typedefs for uint16_t)
which caused the cl_khr_fp16 pragma to be injected into
kernels using cl_ushort which causes errors on platforms
that do not support the cl_khr_fp16 extension.
This adds a new set of methods to the device class allowing
device objects to be partitioned into multiple sub-devices
using the clCreateSubDevices() function.
For now, device partitioning is only supported on systems
with OpenCL version 1.2 (or later).
This adds support for returning a std::vector<T> from the
various get_info<T>() methods. This provides a simpler
interface to get the values in an array returned from one
of the clGet*Info() functions.
This also adds a test using the new API to get the maximum
work item sizes in each dimension for a device.
