Task-based programming offers an elegant way to express units of computation and the
dependencies among them, making it easier to distribute the computational load evenly …

Average programmers struggle to solve performance problems in OpenMP programs with
tasks and parallel for-loops. Existing performance analysis tools visualize OpenMP task …

The development and maintenance of scalable, state-of-the-art applications in High
Performance Computing (HPC) is complex and error-prone. Today, performance debuggers …

Task-based programming provides programmers with an intuitive abstraction to express
parallelism, and runtimes with the flexibility to adapt the schedule and load-balancing to the …

Programmers struggle to understand performance of task-based OpenMP programs since
profiling tools only report thread-based performance. Performance tuning also requires task …

Parallel programming represents the next turning point in how software engineers write
software. Today, low-cost multi-core processors are widely available for both desktop …

Scalasca is a performance analysis tool, which parses the trace of an application run for
certain patterns that indicate performance inefficiencies. In this paper, we present recently …

The introduction of tasks in the OpenMP programming model brings a new level of
parallelism. This also creates new challenges with respect to its meanings and applicability …

OpenMP, a typical shared memory programming paradigm, has been extensively applied in
high performance computing community due to the popularity of multicore architectures in …

In the decade since support for task parallelism was incorporated into OpenMP, its use has
remained limited in part due to concerns about its performance and scalability. This paper …