892 resultados para task dividing


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In older adults, cognitive resources play a key role in maintaining postural stability. In the present study, we evaluated whether increasing postural instability using sway referencing induces changes in resource allocation in dual-task performance leading older adults to prioritize the more age-salient posture task over a cognitive task. Young and older adults participated in the study which comprised two sessions. In the first session, three posture tasks (stable, sway reference visual, sway reference somatosensory) and a working memory task (n-back) were examined. In the second session, single- and dual-task performance of posture and memory were assessed. Postural stability improved with session. Participants were more unstable in the sway reference conditions, and pronounced age differences were observed in the somatosensory sway reference condition. In dual-task performance on the stable surface, older adults showed an almost 40% increase in instability compared to single-task. However, in the sway reference somatosensory condition, stability was the same in single- and dual-task performance, whereas pronounced (15%) costs emerged for cognition. These results show that during dual-tasking while standing on a stable surface, older adults have the flexibility to allow an increase in instability to accommodate cognitive task performance. However, when instability increases by means of compromising somatosensory information, levels of postural control are kept similar in single- and dual-task, by utilizing resources otherwise allocated to the cognitive task. This evidence emphasizes the flexible nature of resource allocation, developed over the life-span to compensate for age-related decline in sensorimotor and cognitive processing.

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We investigate dynamic posture control and working memory (NBack) retest practice in young and older adults, focusing on older adults' potential for improvement in the component tasks but more importantly in dual-task performance. Participants performed the 2 tasks in 11 sessions under single- and dual-task conditions. Posture improvement was observed with retest practice for both groups. Increase in cognitive load after initial practice led to greater dual-task costs in both tasks in older adults and higher costs in memory in young adults. With continued practice, costs were reduced by both groups; however, the 2 groups focused improvement on different tasks: Older adults focused on posture but young adults on cognition. These results emphasize older adults' potential for improvement in dual-task performance and their flexibility to utilize the practice gains in posture to optimize cognitive performance.

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This study used a virtual simulated 3vs3 rugby task to investigate whether gaps opening in particular running channels promote different actions by the ball-carrier player and whether an effect of rugby expertise is verified. We manipulated emergent gaps in three different locations: gap1 in the participant’s own running channel, gap 2 in the 1st receiver's running channel, and gap3 in the 2nd receiver's running channel. Recreational, intermediate, professional and non-rugby players performed the task. They could i) run with the ball, ii) make a short pass, or iii) make a long pass. All actions were digitally recorded. Results revealed that the emergence of gaps in the defensive line with respect to the participant’s own position significantly influenced action selection. Namely, ‘run’ was most often the action performed in gap 1, ‘short pass’ in gap 2, and ‘long pass’ in gap 3 trials. Furthermore, a strong positive relationship between expertise and task achievement was found.

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Absence of leftward bias in a line bisection task is often used as a clinical hemispheric indicator, but the effect is not uniform in a normal population. Sex, handedness, and strategy variables affect the strength and direction of any bias.

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Objective: Previous studies with patients diagnosed with Major Depressive Disorder (MDD) revealed deficits in working memory and executive functions. In the present study we investigated whether patients with MDD have the ability to allocate cognitive resources in dual task performance of a highly challenging cognitive task (working memory) and a task that is seemingly automatic in nature (postural control). Method: Fifteen young (18–35 years old) patients with MDD and 24 healthy age-matched controls performed a working memory task and two postural control tasks (standing on a stable or on a moving platform) both separately (single task) and concurrently (dual task). Results: Postural stability under single task conditions was similar in the two groups, and in line with earlier studies, MDD patients recalled fewer working memory items than controls. To equate working memory challenges for patients and controls, task difficulty (number of items presented) in dual task was individually adjusted such that accuracy of working memory performance was similar for the two groups under single task conditions. Patients showed greater postural instability in dual task performance on the stable platform, and more importantly when posture task difficulty increased (moving platform) they showed deficits in both working memory accuracy and postural stability compared with healthy controls. Conclusions: We interpret our results as evidence for executive control deficits in MDD patients that affect their task coordination. In multitasking, these deficits affect not only cognitive but also sensorimotor task performance.

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The prevalence of multicore processors is bound to drive most kinds of software development towards parallel programming. To limit the difficulty and overhead of parallel software design and maintenance, it is crucial that parallel programming models allow an easy-to-understand, concise and dense representation of parallelism. Parallel programming models such as Cilk++ and Intel TBBs attempt to offer a better, higher-level abstraction for parallel programming than threads and locking synchronization. It is not straightforward, however, to express all patterns of parallelism in these models. Pipelines are an important parallel construct, although difficult to express in Cilk and TBBs in a straightfor- ward way, not without a verbose restructuring of the code. In this paper we demonstrate that pipeline parallelism can be easily and concisely expressed in a Cilk-like language, which we extend with input, output and input/output dependency types on procedure arguments, enforced at runtime by the scheduler. We evaluate our implementation on real applications and show that our Cilk-like scheduler, extended to track and enforce these dependencies has performance comparable to Cilk++.

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Cognitive and neurophysiological correlates of arithmetic calculation, concepts, and applications were examined in 41 adolescents, ages 12-15 years. Psychological and task-related EEG measures which correctly distinguished children who scored low vs. high (using a median split) in each arithmetic subarea were interpreted as indicative of processes involved. Calculation was related to visual-motor sequencing, spatial visualization, theta activity measured during visual-perceptual and verbal tasks at right- and left-hemisphere locations, and right-hemisphere alpha activity measured during a verbal task. Performance on arithmetic word problems was related to spatial visualization and perception, vocabulary, and right-hemisphere alpha activity measured during a verbal task. Results suggest a complex interplay of spatial and sequential operations in arithmetic performance, consistent with processing model concepts of lateralized brain function.

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Task-based dataflow programming models and runtimes emerge as promising candidates for programming multicore and manycore architectures. These programming models analyze dynamically task dependencies at runtime and schedule independent tasks concurrently to the processing elements. In such models, cache locality, which is critical for performance, becomes more challenging in the presence of fine-grain tasks, and in architectures with many simple cores.

This paper presents a combined hardware-software approach to improve cache locality and offer better performance is terms of execution time and energy in the memory system. We propose the explicit bulk prefetcher (EBP) and epoch-based cache management (ECM) to help runtimes prefetch task data and guide the replacement decisions in caches. The runtimem software can use this hardware support to expose its internal knowledge about the tasks to the architecture and achieve more efficient task-based execution. Our combined scheme outperforms HW-only prefetchers and state-of-the-art replacement policies, improves performance by an average of 17%, generates on average 26% fewer L2 misses, and consumes on average 28% less energy in the components of the memory system.

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Task dataflow languages simplify the specification of parallel programs by dynamically detecting and enforcing dependencies between tasks. These languages are, however, often restricted to a single level of parallelism. This language design is reflected in the runtime system, where a master thread explicitly generates a task graph and worker threads execute ready tasks and wake-up their dependents. Such an approach is incompatible with state-of-the-art schedulers such as the Cilk scheduler, that minimize the creation of idle tasks (work-first principle) and place all task creation and scheduling off the critical path. This paper proposes an extension to the Cilk scheduler in order to reconcile task dependencies with the work-first principle. We discuss the impact of task dependencies on the properties of the Cilk scheduler. Furthermore, we propose a low-overhead ticket-based technique for dependency tracking and enforcement at the object level. Our scheduler also supports renaming of objects in order to increase task-level parallelism. Renaming is implemented using versioned objects, a new type of hyper object. Experimental evaluation shows that the unified scheduler is as efficient as the Cilk scheduler when tasks have no dependencies. Moreover, the unified scheduler is more efficient than SMPSS, a particular implementation of a task dataflow language.