For efficient task execution, environment knowledge is maintained in the memory.
In multiprocessor SoC performance evaluation, simulating the profiled or estimated execution times (or number of operations) of tasks on abstract HW resource models is an effective way of observing combined effects of task execution times, mapping, scheduling, and HW platform parameters on resulting task response times, response time jitters, and processing element utilizations.
Hybrid-PuReMD uses an effective task-parallel implementation by overlapping the execution of bonded interactions on CPU and non-bonded and charge equilibration computations on the GPU.
We suggest the algorithm to quantitatively analyze the total task execution time for effective task migration.
Pipeline programming requires effective task management, particularly the ability to launch processes and wait for processes to finish execution before starting others.
The primary contribution of our tool is that it demonstrates an effective visualization and interaction design for rapidly exploring pupillary response in relation to models of task execution, thereby reducing the analysis effort.
Empirical research has reported that subjects provided with graphical formats are more effective in trend, pattern and time sequence data detection, (e.g. [12,68,77]) and in task execution in terms of processing time (e.g. [31,32,44]).
Thus, although selecting an appropriate set of responses must be a core component of implementing an effective task set, the ability to do so appears dissociable from other aspects of task preparation and execution that are reflected in key neural and behavioral measures of task switching studied here.
Therefore, working memory drives efficient inhibition by sustaining task instructions and appropriate responses throughout task execution.
The uncertainty of the task execution time is also considered.
