Sentence examples for communication between tasks from inspiring English sources

For instance, MPI [29] allows the parallel execution of tasks, but was developed for much more complex parallel applications, with high data communication between tasks.

The most notable features of GridGain we use are: tasks and jobs modeled according to the MapReduce paradigm, communication between tasks and jobs, as well as on-demand class loading.

To model this kind of applications we consider a Data Flow Graph (DFG) (an example is depicted in Figure 2) which is a directed acyclic graph where nodes are processing functions and edges describe communication between tasks (data dependencies between tasks).

This covers the segmentation of the application into tasks, the cooperation and communication between these tasks, the suitability of the processor cores for each of these tasks, etc.

Like the compute fabric, the communication structures between tasks can be abstracted by the compute model to simplify the design process.

In this paper, we present a general framework of partitioning an application comprised of hard real-time tasks with precedence constraints onto multiple virtual processors in consideration of communication latencies between tasks.

This allows to set up the communication links between tasks and to determine cooperating tasks.

Unreliable and short-term connectivity can increase communication cost due to frequent failure and activation of links, and ineffective resource allocation can increase communication cost due to multi hop communication between dependent tasks.

On one hand, a low computation to communication ratio (fine-grain parallelism) facilitates load balancing, as relatively small amounts of computational work are done between communication events but this can imply high communication overhead and less opportunity for performance enhancement, because communication and synchronization between tasks may take longer than the computation.

In the deconvolution step, the deconvolution of different voxels are ideally parallel tasks, so that there is little effort required to separate the problem into parallel tasks and there is no dependency or communication between those parallel tasks, parallel implementation can be easily achieved.

We address the issue of task communication between multi-rate, mixed-criticality tasks, and propose a deterministic lossless communication model.