Openmp application program interface manual

IEEE 16th Int. Analyzing the scalability behavior and the overheads of Open-MP applications is an important step in the development process of scientific software.

Unfortunately, few tools are available that allow an exact quantification of OpenMP related overheads and scalability characteristics. We present a met Abstract - Cited by 5 1 self - Add to MetaCart Analyzing the scalability behavior and the overheads of Open-MP applications is an important step in the development process of scientific software.

We present a methodology in which we define four overhead categories that we can quantify exactly and describe a tool that implements this methodology. Large scale parallel simulations are fundamental tools for engineers and scientists. Consequently, it is critical to develop both programming models and tools that enhance development time productivity, enable harnessing of massively-parallel systems, and to guide the diagnosis of poorly scaling pro Abstract - Cited by 2 1 self - Add to MetaCart Large scale parallel simulations are fundamental tools for engineers and scientists.

Consequently, it is critical to develop both programming models and tools that enhance development time productivity, enable harnessing of massively-parallel systems, and to guide the diagnosis of poorly scaling programs.

This thesis addresses this challenge in two ways. First, we show that Co-array Fortran CAF , a shared-memory parallel programming model, can be used to write scientific codes that exhibit high performance on modern parallel systems. Second, we describe a novel technique for analyzing parallel program performance and identifying scalability bottlenecks, and apply it across multiple programming models.

Although the message passing parallel programming model provides both portability and high performance, it is cumbersome to program. CAF eases this burden by providing a partitioned global address space, but has before now only been implemented on shared-memory machines.

We designed and imple-. Tuning parallel code can be a time-consuming and difficult task. We present our approach to automate the performance analysis of OpenMP applications that is based on the notion of performance properties. A section of code that is to be executed in parallel is marked by a special directive omp pragma. When the execution reaches a parallel section marked by omp pragma , this directive will cause slave threads to form. Each thread executes the parallel section of the code independently.

When a thread finishes, it joins the master. When all threads finish, the master continues with code following the parallel section. The ID of the master thread is 0. Why OpenMP? More efficient, and lower-level parallel code is possible, however OpenMP hides the low-level details and allows the programmer to describe the parallel code with high-level constructs, which is as simple as it can get.

A quick search with google reveals that the native apple compiler clang is installed without openmp support. When you installed gcc it probably got installed without openmp support. Then I asked brew to install gcc: 3. For example, a serial addition reduction may have a different pattern of addition associations than a parallel reduction.

These different associations may change the results of floating-point addition. OpenMP provides a relaxed-consistency, shared-memory model of parallelism. All OpenMP threads have access to a place to store and to retrieve variables, called the memory. The OpenMP runtime system invokes this callback after a task exits a critical region. The OpenMP runtime system invokes this callback after a task completes an ordered region.

The OpenMP runtime system invokes this callback after a task completes an atomic region. If an atomic block is implemented using a hardware instruction, then an OpenMP runtime may choose to never report this event. However, if an atomic region is implemented using any mechanism that might involve spinning in software, then an OpenMP runtime developer should consider reporting this event if the time or effort a thread invests in waiting or retries exceeds a constant threshold defined by the developer.

Examples of spinning in software include spin waiting on a critical section used to implement atomics, or retrying atomic operations implemented using hardware primitives that may fail. The OpenMP runtime system invokes this callback, after an implicit task is fully initialized and before the task executes its work.

This callback executes in the context of the implicit task. The callback executes in the context of the implicit task. The OpenMP runtime system invokes this callback after it suspends one task and before it resumes another task. This callback executes in the environment of the resumed task.

The OpenMP runtime system invokes this callback just after this task initializes the nest lock. The OpenMP runtime system invokes this callback just before this task destroys the nest lock. The OpenMP runtime system invokes this callback after the parallel loop is initialized for this thread and before this thread executes a first loop iteration. This callback executes in the context of the task.

The OpenMP runtime system invokes this callback after the last loop iteration for this thread ex- ecutes and before this thread executes the loop barrier wait or the statement following the loop nowait.

The OpenMP runtime system invokes this callback after a parallel section is initialized for this thread and before this thread executes a first section. The OpenMP runtime system invokes this callback after the last section for this thread is executed and before this thread executes the section barrier wait or the statement following the section con- struct nowait.

The OpenMP runtime system invokes this callback after the single construct is initialized for this thread and before this thread executes the code block of the single region. The OpenMP runtime system invokes this callback after this thread executes the code code block of the single region and before this thread executes the single barrier wait or the statement following the single construct nowait.

The OpenMP runtime system invokes this callback after the single construct is initialized for this thread and before this thread would have executed the code block of the single region if this thread had been selected. The OpenMP runtime system invokes this callback after this thread would have executed the code block of the single region if this thread had been selected and before this thread executes the single barrier wait or the statement following the single construct nowait.

The OpenMP runtime system invokes this callback after the master section is initialized for this thread and before this thread executes the master code. This callback executes in the context of the master task. The OpenMP runtime system invokes this callback after the master code is executed and before this thread executes the statement following the master construct. The OpenMP runtime system invokes this callback before this thread starts executing the barrier construct.

The OpenMP runtime system invokes this callback after this thread completes executing the bar- rier construct. The OpenMP runtime system invokes this callback before this thread starts executing the taskwait construct. The OpenMP runtime system invokes this callback after this thread completes executing the taskwait construct. The OpenMP runtime system invokes this callback before this thread starts executing the taskgroup construct.

The OpenMP runtime system invokes this callback after this thread completes executing the taskgroup construct. The OpenMP runtime system invokes this callback just after this task acquires the lock. The OpenMP runtime system invokes this callback just after this task acquires a nest lock for the first time.

The OpenMP runtime system invokes this callback after a nest lock has been released but is still owned by this task. If a nest lock was acquired n times by the same task, this callback occurs for the inner n-1 releases. The OpenMP runtime system invokes this callback just after this task acquires the nest lock that was already owed by this task.

The OpenMP runtime system invokes this callback just after this task enters the critical region. The OpenMP runtime system invokes this callback just after this task enters the ordered region. The OpenMP runtime system invokes this callback just after this task enters the atomic region.

The OpenMP runtime system invokes this callback just after performing a flush operation. If there is no callback associated with this event, the OpenMP runtime initializes the structure value field to 0.

The address of the structure can also be retrieved on demand, e. For example, when a thread is waiting for a lock, this structure identifies the address of the lock. This structure is undefined when a thread is not in a wait state. While the value of the structure is preserved over the lifetime of the task, tools should not assume that the address of a structure remains constant over its lifetime.

Frame data is passed to some callbacks; it can also be retrieved for a task e. Frame data contains two components:. This field points to the stack frame of the runtime procedure that called the user code.

This value is NULL until just before the task exits the runtime. This field points to the stack frame of the runtime procedure called by a task to re-enter the runtime. This value is NULL until just after the task re-enters the runtime. Tools must be prepared to handle samples that occur in this brief window. Inquiry functions retrieve data from the execution environment for the tools. All inquiry functions are async signal safe. An OpenMP runtime system is allowed to support other states in addition to those described herein.