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‎Chap_SIMD.tex‎

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\pagebreak
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\chapter{SIMD}
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\cchapter{SIMD}{SIMD}
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\label{chap:simd}
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Single instruction, multiple data (SIMD) is a form of parallel execution
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Loops without loop-carried backward dependency (or with dependency preserved using
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ordered simd) are candidates for vectorization by the compiler for
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execution with SIMD units. In addition, with state-of-the-art vectorization
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technology and \code{declare simd} construct extensions for function vectorization
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technology and \code{declare simd} directive extensions for function vectorization
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in the OpenMP 4.5 specification, loops with function calls can be vectorized as well.
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The basic idea is that a scalar function call in a loop can be replaced by a vector version
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of the function, and the loop can be vectorized simultaneously by combining a loop
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%\code{parallel for simd}).
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%===== Examples Sections =====
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\input{SIMD/SIMD}
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\input{SIMD/linear_modifier}
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‎Chap_affinity.tex‎

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\pagebreak
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\chapter{OpenMP Affinity}
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\cchapter{OpenMP Affinity}{affinity}
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\label{chap:openmp_affinity}
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OpenMP Affinity consists of a \code{proc\_bind} policy (thread affinity policy) and a specification of
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%which sets \code{OMP\_PLACES} specifically for the MPI process.
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Threads of a team are positioned onto places in a compact manner, a
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scattered distribution, or onto the master's place, by setting the
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scattered distribution, or onto the primary thread's place, by setting the
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\code{OMP\_PROC\_BIND} environment variable or the \code{proc\_bind} clause to
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\plc{close}, \plc{spread}, or \plc{master}, respectively. When
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\code{close}, \code{spread}, or \code{primary} (\code{master} has been deprecated), respectively. When
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\code{OMP\_PROC\_BIND} is set to FALSE no binding is enforced; and
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when the value is TRUE, the binding is implementation defined to
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a set of places in the \code{OMP\_PLACES} variable or to places
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defined by the implementation if the \code{OMP\_PLACES} variable
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is not set.
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is not set.
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The \code{OMP\_PLACES} variable can also be set to an abstract name
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(\plc{threads}, \plc{cores}, \plc{sockets}) to specify that a place is
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(\code{threads}, \code{cores}, \code{sockets}) to specify that a place is
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either a single hardware thread, a core, or a socket, respectively.
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This description of the \code{OMP\_PLACES} is most useful when the
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number of threads is equal to the number of hardware thread, cores
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or sockets. It can also be used with a \plc{close} or \plc{spread}
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or sockets. It can also be used with a \code{close} or \code{spread}
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distribution policy when the equality doesn't hold.
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% thread # 0 * * * * _ _ _ _ _ _ _ _ #mask for thread 0
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% thread # 0 _ _ _ _ * * * * _ _ _ _ #mask for thread 1
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% thread # 0 _ _ _ _ _ _ _ _ * * * * #mask for thread 2
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%===== Examples Sections =====
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\input{affinity/affinity}
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\input{affinity/task_affinity}
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\input{affinity/affinity_display}
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\input{affinity/affinity_query}
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‎Chap_data_environment.tex‎

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\pagebreak
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\chapter{Data Environment}
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\cchapter{Data Environment}{data_environment}
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\label{chap:data_environment}
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The OpenMP \plc{data environment} contains data attributes of variables and
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objects. Many constructs (such as \code{parallel}, \code{simd}, \code{task})
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map regions and/or accumulative (unstructured) mappings, determines the operation.
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Details of the \code{map} clause and reference count operation are specified
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in the \plc{map Clause} subsection of the OpenMP Specifications document.
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%===== Examples Sections =====
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\input{data_environment/threadprivate}
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\input{data_environment/default_none}
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\input{data_environment/private}
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\input{data_environment/fort_loopvar}
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\input{data_environment/fort_sp_common}
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\input{data_environment/fort_sa_private}
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\input{data_environment/carrays_fpriv}
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\input{data_environment/lastprivate}
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\input{data_environment/reduction}
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\input{data_environment/udr}
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\input{data_environment/scan}
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\input{data_environment/copyin}
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\input{data_environment/copyprivate}
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\input{data_environment/cpp_reference}
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\input{data_environment/associate}
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‎Chap_devices.tex‎

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\pagebreak
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\chapter{Devices}
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\cchapter{Devices}{devices}
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\label{chap:devices}
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The \code{target} construct consists of a \code{target} directive
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pre-4.5 code; it is a necessary element for asynchronous
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execution of the \code{target} region when using the new \code{nowait}
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clause introduced in OpenMP 4.5.
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%===== Examples Sections =====
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\input{devices/target}
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\input{devices/target_defaultmap}
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\input{devices/target_pointer_mapping}
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\input{devices/target_structure_mapping}
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\input{devices/target_fort_allocatable_array_mapping}
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\input{devices/array_sections}
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\input{devices/array_shaping}
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\input{devices/target_mapper}
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\input{devices/target_data}
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\input{devices/target_unstructured_data}
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\input{devices/target_update}
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\input{devices/target_associate_ptr}
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\input{devices/declare_target}
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\input{devices/teams}
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\input{devices/async_target_depend}
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\input{devices/async_target_with_tasks}
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\input{devices/async_target_nowait}
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\input{devices/async_target_nowait_depend}
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\input{devices/device}
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‎Chap_directives.tex‎

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\cchapter{OpenMP Directive Syntax}{directives}
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\label{chap:directive_syntax}
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OpenMP \emph{directives} use base-language mechanisms to specify OpenMP program behavior.
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In C code, the directives are formed exclusively with pragmas, whereas in C++
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code, directives are formed from either pragmas or attributes.
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Fortran directives are formed with comments in free form and fixed form sources (codes).
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All of these mechanism allow the compilation to ignore the OpenMP directives if
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OpenMP is not supported or enabled.
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The OpenMP directive is a combination of the base-language mechanism and a \plc{directive-specification},
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as shown below. The \plc{directive-specification} consists
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of the \plc{directive-name} which may seldomly have arguments,
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followed by optional \plc{clauses}. Full details of the syntax can be found in the OpenMP Specification.
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Illustrations of the syntax is given in the examples.
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The formats for combining a base-language mechanism and a \plc{directive-specification} are:
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C/C++ pragmas
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\begin{indentedcodelist}
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\code{\#pragma omp} \plc{directive-specification}
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\end{indentedcodelist}
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C++ attributes
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\begin{indentedcodelist}
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\code{[[omp :: directive(} \plc{directive-specification} \code{)]]}
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\code{[[using omp : directive(} \plc{directive-specification} \code{)]]}
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\end{indentedcodelist}
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Fortran comments
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\begin{indentedcodelist}
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\code{!\$omp} \plc{directive-specification}
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\end{indentedcodelist}
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where \code{c\$omp} and \code{*\$omp} may be used in Fortran fixed form sources.
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%===== Examples Sections =====
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\input{directives/pragmas}
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\input{directives/attributes}
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\input{directives/fixed_format_comments}
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\input{directives/free_format_comments}
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‎Chap_loop_transformations.tex‎

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\cchapter{Loop Transformations}{loop_transformations}
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\label{chap:loop_transformations}
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To obtain better performance on a platform, code may need to be restructured
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relative to the way it is written (which is often for best readability).
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User-directed loop transformations accomplish this goal by providing a means
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to separate code semantics and its optimization.
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A loop transformation construct states that a transformation operation is to be
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performed on set of nested loops. This directive approach can target specific loops
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for transformation, rather than applying more time-consuming general compiler
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heuristics methods with compiler options that may not be able to discover
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optimal transformations.
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Loop transformations can be augmented by preprocessor support or OpenMP \code{metadirective}
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directives, to select optimal dimension and size parameters for specific platforms,
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facilitating a single code base for multiple platforms.
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Moreover, directive-based transformations make experimenting easier:
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whereby specific hot spots can be affected by transformation directives.
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%===== Examples Sections =====
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\input{loop_transformations/tile}
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\input{loop_transformations/unroll}
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‎Chap_memory_model.tex‎

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\pagebreak
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\chapter{Memory Model}
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\cchapter{Memory Model}{memory_model}
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\label{chap:memory_model}
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OpenMP provides a shared-memory model that allows all threads on a given
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% in \plc{atomic Construct} subsection of the OpenMP Specifications document).
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% Examples 1-3 show the difficulty of synchronizing threads through \code{flush} and \code{atomic} directives.
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%===== Examples Sections =====
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\input{memory_model/mem_model}
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\input{memory_model/allocators}
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\input{memory_model/fort_race}
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‎Chap_ompt_interface.tex‎

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\cchapter{OMPT Interface}{ompt_interface}
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\label{chap:ompt_interface}
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OMPT defines mechanisms and an API for interfacing with tools in the OpenMP program.
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The OMPT API provides the following functionality:
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\begin{itemize}
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\addtolength{\itemindent}{1cm}
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\item examines the state associated with an OpenMP thread
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\item interprets the call stack of an OpenMP thread
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\item receives notification about OpenMP events
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\item traces activity on OpenMP target devices
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\item assesses implementation-dependent details
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\item controls a tool from an OpenMP application
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\end{itemize}
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The following sections will illustrate basic mechanisms and operations of the OMPT API.
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\input{ompt_interface/ompt_start}

‎Chap_parallel_execution.tex‎

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\pagebreak
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\chapter{Parallel Execution}
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\cchapter{Parallel Execution}{parallel_execution}
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\label{chap:parallel_execution}
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A single thread, the \plc{initial thread}, begins sequential execution of
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forming a parallel region. An \plc{initial thread} encountering a \code{parallel}
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region forks (creates) a team of threads at the beginning of the
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\code{parallel} region, and joins them (removes from execution) at the
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end of the region. The initial thread becomes the master thread of the team in a
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end of the region. The initial thread becomes the primary thread of the team in a
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\code{parallel} region with a \plc{thread} number equal to zero, the other
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threads are numbered from 1 to number of threads minus 1.
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A team may be comprised of just a single thread.
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parallel region. The task that creates a parallel region is suspended while the
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tasks of the team are executed. A thread is tied to its task; that is,
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only the thread assigned to the task can execute that task. After completion
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of the \code{parallel} region, the master thread resumes execution of the generating task.
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of the \code{parallel} region, the primary thread resumes execution of the generating task.
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%After the \code{parallel} region the master thread becomes the initial
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%After the \code{parallel} region the primary thread becomes the initial
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%thread again, and continues to execute the \plc{sequential part}.
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Any task within a \code{parallel} region is allowed to encounter another
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the number of threads becomes an upper limit for the number of threads to be
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provided by the OpenMP runtime.
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\pagebreak
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%\pagebreak
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\bigskip
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WORKSHARING CONSTRUCTS
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A worksharing construct distributes the execution of the associated region
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by threads of the team.
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\bigskip
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MASTER CONSTRUCT
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MASKED CONSTRUCT
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The \code{masked} construct is not a worksharing construct. The \code{masked} region is
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executed only by the primary thread. There is no implicit barrier (and flush)
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at the end of the \code{masked} region; hence the other threads of the team continue
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execution beyond code statements beyond the \code{masked} region.
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The \code{master} contruct, which has been deprecated in OpenMP 5.1, has identical semantics
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to the \code{masked} contruct with no \code{filter} clause.
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%===== Examples Sections =====
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\input{parallel_execution/ploop}
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\input{parallel_execution/parallel}
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\input{parallel_execution/host_teams}
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\input{parallel_execution/nthrs_nesting}
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\input{parallel_execution/nthrs_dynamic}
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\input{parallel_execution/fort_do}
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\input{parallel_execution/nowait}
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\input{parallel_execution/collapse}
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\input{parallel_execution/linear_in_loop}
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\input{parallel_execution/psections}
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\input{parallel_execution/fpriv_sections}
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\input{parallel_execution/single}
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\input{parallel_execution/workshare}
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\input{parallel_execution/masked}
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\input{parallel_execution/loop}
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\input{parallel_execution/pra_iterator}
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\input{parallel_execution/set_dynamic_nthrs}
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\input{parallel_execution/get_nthrs}
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The \code{master} construct is not a worksharing construct. The master region is
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is executed only by the master thread. There is no implicit barrier (and flush)
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at the end of the \code{master} region; hence the other threads of the team continue
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execution beyond code statements beyond the \code{master} region.

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