Nancy M. Amato

TL;DR: This work presents an algorithm called Topological Nearest-Neighbor Filtering, which employs a workspace decomposition to select a topologically relevant set of candidate neighbor configurations as a pre-processing step for a nearest-neighbor algorithm.

TL;DR: This work presents an approach to transparently (without programmer intervention) allow fine-grained graph algorithms to utilize algorithmic communication reduction optimizations and presents an optimization for small-world scale-free graphs wherein hub vertices are represented in a similar hierarchical manner, which is exploited to increase parallelism and reduce communication.

TL;DR: This study presents a detailed comparison of two architectures, the HP V-Class and the SGI Origin 2000, and presents the impact of processor design, cache/memory hierarchies and coherence protocol optimizations on the memory system performance of these multiprocessors.

TL;DR: In this paper, the main societal opportunities identified, the associated challenges to deliver desired solutions and a presentation of efforts to be undertaken to ensure that US will continue to be a leader in robotics both in terms of research innovation, adoption of the latest technology, and adoption of appropriate policy frameworks that ensure that the technology is utilized in a responsible fashion.

TL;DR: It is shown that signi cant speedups can be obtained with relatively little on the part of the developer by employing new connection strategies and more intelligent ways of invoking and utilizing existing o -the-shelf collision detection packages.