Narasimha, Lord of Transitions, Transformations, and Theater Festivals: God and Evil in Hindu Cosmology, Myth, and Practice

This paper focuses on the multi-faceted nature of the divine depicted in Narasimha and the unique perspectives on God and evil offered by the myths of Narasimha, which is also subliminally represented within the religious practice and performance traditions associated with Narasimha

Dynamics of Attention in Depth: Evidence from Mutli-Element Tracking

The allocation of attention in depth is examined using a multi-element tracking paradigm. Observers are required to track a predefined subset of from two to eight elements in displays containing up to sixteen identical moving elements. We first show that depth cues, such as binocular disparity and occlusion through T-junctions, improve performance in a multi-element tracking task in the case where element boundaries are allowed to intersect in the depiction of motion in a single fronto-parallel plane. We also show that the allocation of attention across two perceptually distinguishable planar surfaces either fronto-parallel or receding at a slanting angle and defined by coplanar elements, is easier than allocation of attention within a single surface. The same result was not found when attention was required to be deployed across items of two color populations rather than of a single color. Our results suggest that, when surface information does not suffice to distinguish between targets and distractors that are embedded in these surfaces, division of attention across two surfaces aids in tracking moving targets.National Science Foundation (IRI-94-01659); Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657

Attention in Depth: Disparity and Occlusion Cues Facilitate Multi-Element Visual Tracking

Human observers can track up to five moving targets in a display with ten identical elements (Pylyshyn and Storm, 1988; Yantis, 1992). Previous experiments manipulated element trajectories to prevent intersections of element boundaries, evidently in the belief that transient overlaps among homogeneous elements make the task too hard. We examine whether depth cues such as occlusion (T-junctions) and disparity affect performance in a tracking task when element boundaries, as projected onto the two-dimensional plane of the monitor screen, are allowed to intersect. Elements move smoothly in depth, as well as in horizontal and vertical position, throughout a 7-second tracking period. A probe is then flashed, and subjects report whether the flash occurred on a target or on a non-target. Overlapping circular objects form T-junctions when shaded to appear like spheres or figure eight regions when rendered as disks. Two factors, disparity and T-junctions, are considered. Results from eight naive observers show that performance improves for displays with depth information (T-junctions or disparity), suggesting that depth cues are useful for multi-element tracking.National Science Foundation (IRI-94-01659); Office of Naval Research (N00014-92-J-1309, N00014-95-1-0657, N00014-94-1-0597, N00014-95-1-0409

Spacing affects some but not all visual searches: Implications for theories of attention and crowding

We investigated the effect of varying interstimulus spacing on an upright among inverted face search and a red–green among green–red bisected disk search. Both tasks are classic examples of serial search; however, spacing affects them very differently: As spacing increased, face discrimination performance improved significantly, whereas performance on the bisected disks remained poor. (No effect of spacing was observed for either a red among green or an L among + search tasks, two classic examples of parallel search.) In a second experiment, we precued the target location so that attention was no longer a limiting factor: Both serial search tasks were now equally affected by spacing, a result we attribute to a more classical form of crowding. The observed spacing effect in visual search suggests that for certain tasks, serial search may result from local neuronal competition between target and distractors, soliciting attentional resources; in other cases, serial search must occur for another reason, for example, because an item-by-item, attention-mediated recognition must take place. We speculate that this distinction may be based on whether or not there exist neuronal populations tuned to the relevant target–distractor distinction, and we discuss the possible relations between this spacing effect in visual search and other forms of crowding

SQUASH: Simple QoS-Aware High-Performance Memory Scheduler for Heterogeneous Systems with Hardware Accelerators

Modern SoCs integrate multiple CPU cores and Hardware Accelerators (HWAs) that share the same main memory system, causing interference among memory requests from different agents. The result of this interference, if not controlled well, is missed deadlines for HWAs and low CPU performance. State-of-the-art mechanisms designed for CPU-GPU systems strive to meet a target frame rate for GPUs by prioritizing the GPU close to the time when it has to complete a frame. We observe two major problems when such an approach is adapted to a heterogeneous CPU-HWA system. First, HWAs miss deadlines because they are prioritized only close to their deadlines. Second, such an approach does not consider the diverse memory access characteristics of different applications running on CPUs and HWAs, leading to low performance for latency-sensitive CPU applications and deadline misses for some HWAs, including GPUs. In this paper, we propose a Simple Quality of service Aware memory Scheduler for Heterogeneous systems (SQUASH), that overcomes these problems using three key ideas, with the goal of meeting deadlines of HWAs while providing high CPU performance. First, SQUASH prioritizes a HWA when it is not on track to meet its deadline any time during a deadline period. Second, SQUASH prioritizes HWAs over memory-intensive CPU applications based on the observation that the performance of memory-intensive applications is not sensitive to memory latency. Third, SQUASH treats short-deadline HWAs differently as they are more likely to miss their deadlines and schedules their requests based on worst-case memory access time estimates. Extensive evaluations across a wide variety of different workloads and systems show that SQUASH achieves significantly better CPU performance than the best previous scheduler while always meeting the deadlines for all HWAs, including GPUs, thereby largely improving frame rates