1,200 research outputs found
GraphH: High Performance Big Graph Analytics in Small Clusters
It is common for real-world applications to analyze big graphs using
distributed graph processing systems. Popular in-memory systems require an
enormous amount of resources to handle big graphs. While several out-of-core
approaches have been proposed for processing big graphs on disk, the high disk
I/O overhead could significantly reduce performance. In this paper, we propose
GraphH to enable high-performance big graph analytics in small clusters.
Specifically, we design a two-stage graph partition scheme to evenly divide the
input graph into partitions, and propose a GAB (Gather-Apply-Broadcast)
computation model to make each worker process a partition in memory at a time.
We use an edge cache mechanism to reduce the disk I/O overhead, and design a
hybrid strategy to improve the communication performance. GraphH can
efficiently process big graphs in small clusters or even a single commodity
server. Extensive evaluations have shown that GraphH could be up to 7.8x faster
compared to popular in-memory systems, such as Pregel+ and PowerGraph when
processing generic graphs, and more than 100x faster than recently proposed
out-of-core systems, such as GraphD and Chaos when processing big graphs
GraphMP: An Efficient Semi-External-Memory Big Graph Processing System on a Single Machine
Recent studies showed that single-machine graph processing systems can be as
highly competitive as cluster-based approaches on large-scale problems. While
several out-of-core graph processing systems and computation models have been
proposed, the high disk I/O overhead could significantly reduce performance in
many practical cases. In this paper, we propose GraphMP to tackle big graph
analytics on a single machine. GraphMP achieves low disk I/O overhead with
three techniques. First, we design a vertex-centric sliding window (VSW)
computation model to avoid reading and writing vertices on disk. Second, we
propose a selective scheduling method to skip loading and processing
unnecessary edge shards on disk. Third, we use a compressed edge cache
mechanism to fully utilize the available memory of a machine to reduce the
amount of disk accesses for edges. Extensive evaluations have shown that
GraphMP could outperform state-of-the-art systems such as GraphChi, X-Stream
and GridGraph by 31.6x, 54.5x and 23.1x respectively, when running popular
graph applications on a billion-vertex graph
A two-phase approach to interactivity enhancement for large-scale distributed virtual environments
Efficient Client-to-Server Assignments for Distributed Virtual Environments
Distributed Virtual Environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently assign the participating clients to servers to enhance users ’ experience in interacting within the DVE. This problem is termed the client assignment problem. In this paper, we propose a two-phase approach, consisting of an initial assignment phase and a refined assignment phase to address this problem. Both phases are shown to be NP-hard, and several heuristic assignment algorithms are then devised based on this two-phase approach. Via extensive simulation studies with realistic settings, we evaluate these algorithms in terms of their performances in enhancing interactivity of the DVE. 1
A microwave active filter for nanosatellite’s receiver front-ends at s-bands
In satellite technology, the communication between space segment and ground segment plays a vital role in the success of the mission. This paper is targeted at study, design and fabrication of a microwave active filter for the receiver front-ends using coupled line filter structure, which can be applied to the nanosatellite’s communication subsystem. The whole active filter module is a combination of a microstrip bandpass filter and a preceding two-stage wideband low noise amplifier using FET devices. The proposed module operates in the frequency range of 2 - 2.4 GHz, which can be divided to 10 frequency slots of about 40 MHz for each. These frequency slots will be used for the S-band multi-frequency receiving function of the ground station, as well as the nanosatellite. The simulated and measured results of this active filter configuration are presented
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