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@@ -55,12 +55,12 @@ This manual documents the usage of StarPU
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@c complex machines with heterogeneous cores/devices
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The use of specialized hardware such as accelerators or coprocessors offers an
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-interesting approach to overcome the physical limits encountered by processor
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+interesting approach to overcome the physical limits encountered by processor
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architects. As a result, many machines are now equipped with one or several
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accelerators (eg. a GPU), in addition to the usual processor(s). While a lot of
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efforts have been devoted to offload computation onto such accelerators, very
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-few attention as been paid to portability concerns on the one hand, and to the
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-possibility of having heterogeneous accelerators and processors to interact.
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+little attention as been paid to portability concerns on the one hand, and to the
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+possibility of having heterogeneous accelerators and processors to interact on the other hand.
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StarPU is a runtime system that offers support for heterogeneous multicore
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architectures, it not only offers a unified view of the computational resources
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@@ -79,8 +79,8 @@ transparently handling low-level issues in a portable fashion.
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@section StarPU in a Nutshell
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From a programming point of view, StarPU is not a new language but a library
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-that execute tasks explicitly submitted by the application. The data that a
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-task manipulate are automatically transferred onto the accelerators so that the
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+that executes tasks explicitly submitted by the application. The data that a
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+task manipulate are automatically transferred onto the accelerator so that the
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programmer does not have to take care of complex data movements. StarPU also
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takes particular care of scheduling those tasks efficiently and allows
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scheduling experts to implement custom scheduling policies in a portable
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@@ -95,7 +95,7 @@ such as a CPU, a CUDA device or a Cell's SPU.
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@c TODO insert illustration f : f_spu, f_cpu, ...
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Another important data structure is the @b{task}. Executing a StarPU task
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-consists in applying a codelet on a data set on one of the architecture on
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+consists in applying a codelet on a data set, on one of the architecture on
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which the codelet is implemented. In addition to the codelet that a task
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implements, it also describes which data are accessed, and how they are
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accessed during the computation (read and/or write).
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@@ -510,12 +510,12 @@ int main(int argc, char **argv)
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@end example
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Before submitting any tasks to StarPU, @code{starpu_init} must be called. The
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-@code{NULL} arguments specifies that we use default configuration. Tasks cannot
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+@code{NULL} argument specifies that we use default configuration. Tasks cannot
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be submitted after the termination of StarPU by a call to
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@code{starpu_shutdown}.
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In the example above, a task structure is allocated by a call to
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-@code{starpu_task_create}. This function only allocate and fills the
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+@code{starpu_task_create}. This function only allocates and fills the
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corresponding structure with the default settings (@pxref{starpu_task_create}),
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but it does not submit the task to StarPU.
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@@ -527,7 +527,7 @@ structure is a wrapper containing a codelet and the piece of data on which the
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codelet should operate.
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The optional ''@code{.cl_arg}'' field is a pointer to a buffer (of size
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-@code{.cl_arg_size}) with some parameters for some parameters for the kernel
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+@code{.cl_arg_size}) with some parameters for the kernel
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described by the codelet. For instance, if a codelet implements a computational
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kernel that multiplies its input vector by a constant, the constant could be
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specified by the means of this buffer.
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@@ -549,7 +549,7 @@ guarantee that asynchronous tasks have been executed before it returns.
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@node Scaling a Vector
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@section Manipulating Data: Scaling a Vector
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-The previous example has shown how to submit tasks, in this section we show how
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+The previous example has shown how to submit tasks. In this section we show how
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StarPU tasks can manipulate data.
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Programmers can describe the data layout of their application so that StarPU is
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@@ -575,7 +575,7 @@ starpu_data_handle tab_handle;
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starpu_register_vector_data(&tab_handle, 0, tab, n, sizeof(float));
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@end example
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-The first argument, called the @b{data handle} is an opaque pointer which
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+The first argument, called the @b{data handle}, is an opaque pointer which
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designates the array in StarPU. This is also the structure which is used to
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describe which data is used by a task.
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@c TODO: what is 0 ?
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@@ -628,7 +628,7 @@ starpu_codelet cl = @{
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The second argument of the @code{scal_func} function contains a pointer to the
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-parameters of the codelet (given in @code{task->cl_arg}), so the we read the
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+parameters of the codelet (given in @code{task->cl_arg}), so that we read the
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constant factor from this pointer. The first argument is an array that gives
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a description of every buffers passed in the @code{task->buffers}@ array, the
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number of which is given by the @code{.nbuffers} field of the codelet structure.
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Cédric Augonnet