185,632 research outputs found
Towards Scalable Visual Exploration of Very Large RDF Graphs
In this paper, we outline our work on developing a disk-based infrastructure
for efficient visualization and graph exploration operations over very large
graphs. The proposed platform, called graphVizdb, is based on a novel technique
for indexing and storing the graph. Particularly, the graph layout is indexed
with a spatial data structure, i.e., an R-tree, and stored in a database. In
runtime, user operations are translated into efficient spatial operations
(i.e., window queries) in the backend.Comment: 12th Extended Semantic Web Conference (ESWC 2015
Efficient Subgraph Matching on Billion Node Graphs
The ability to handle large scale graph data is crucial to an increasing
number of applications. Much work has been dedicated to supporting basic graph
operations such as subgraph matching, reachability, regular expression
matching, etc. In many cases, graph indices are employed to speed up query
processing. Typically, most indices require either super-linear indexing time
or super-linear indexing space. Unfortunately, for very large graphs,
super-linear approaches are almost always infeasible. In this paper, we study
the problem of subgraph matching on billion-node graphs. We present a novel
algorithm that supports efficient subgraph matching for graphs deployed on a
distributed memory store. Instead of relying on super-linear indices, we use
efficient graph exploration and massive parallel computing for query
processing. Our experimental results demonstrate the feasibility of performing
subgraph matching on web-scale graph data.Comment: VLDB201
Sampling-Based Exploration Strategies for Mobile Robot Autonomy
A novel, sampling-based exploration strategy is introduced for Unmanned Ground Vehicles (UGV) to efficiently map large GPS-deprived underground environments. It is compared to state-of-the-art approaches and performs on a similar level, while it is not designed for a specific robot or sensor configuration like the other approaches. The introduced exploration strategy, which is called Random-Sampling-Based Next-Best View Exploration (RNE), uses a Rapidly-exploring Random Graph (RRG) to find possible view points in an area around the robot. They are compared with a computation-efficient Sparse Ray Polling (SRP) in a voxel grid to find the next-best view for the exploration. Each node in the exploration graph built with RRG is evaluated regarding the ability of the UGV to traverse it, which is derived from an occupancy grid map. It is also used to create a topology-based graph where nodes are placed centrally to reduce the risk of collisions and increase the amount of observable space. Nodes that fall outside the local exploration area are stored in a global graph and are connected with a Traveling Salesman Problem solver to explore them later
A Methodology for Efficient Space-Time Adapter Design Space Exploration: A Case Study of an Ultra Wide Band Interleaver
This paper presents a solution to efficiently explore the design space of
communication adapters. In most digital signal processing (DSP) applications,
the overall architecture of the system is significantly affected by
communication architecture, so the designers need specifically optimized
adapters. By explicitly modeling these communications within an effective
graph-theoretic model and analysis framework, we automatically generate an
optimized architecture, named Space-Time AdapteR (STAR). Our design flow inputs
a C description of Input/Output data scheduling, and user requirements
(throughput, latency, parallelism...), and formalizes communication constraints
through a Resource Constraints Graph (RCG). The RCG properties enable an
efficient architecture space exploration in order to synthesize a STAR
component. The proposed approach has been tested to design an industrial data
mixing block example: an Ultra-Wideband interleaver.Comment: ISBN:1-4244-0921-
A Design Methodology for Space-Time Adapter
This paper presents a solution to efficiently explore the design space of
communication adapters. In most digital signal processing (DSP) applications,
the overall architecture of the system is significantly affected by
communication architecture, so the designers need specifically optimized
adapters. By explicitly modeling these communications within an effective
graph-theoretic model and analysis framework, we automatically generate an
optimized architecture, named Space-Time AdapteR (STAR). Our design flow inputs
a C description of Input/Output data scheduling, and user requirements
(throughput, latency, parallelism...), and formalizes communication constraints
through a Resource Constraints Graph (RCG). The RCG properties enable an
efficient architecture space exploration in order to synthesize a STAR
component. The proposed approach has been tested to design an industrial data
mixing block example: an Ultra-Wideband interleaver.Comment: ISBN : 978-1-59593-606-
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