38,265 research outputs found
Communication Bottlenecks in Scale-Free Networks
We consider the effects of network topology on the optimality of packet
routing quantified by , the rate of packet insertion beyond which
congestion and queue growth occurs. The key result of this paper is to show
that for any network, there exists an absolute upper bound, expressed in terms
of vertex separators, for the scaling of with network size ,
irrespective of the routing algorithm used. We then derive an estimate to this
upper bound for scale-free networks, and introduce a novel static routing
protocol which is superior to shortest path routing under intense packet
insertion rates.Comment: 5 pages, 3 figure
A Systemic Receptor Network Triggered by Human cytomegalovirus Entry
Virus entry is a multistep process that triggers a variety of cellular
pathways interconnecting into a complex network, yet the molecular complexity
of this network remains largely unsolved. Here, by employing systems biology
approach, we reveal a systemic virus-entry network initiated by human
cytomegalovirus (HCMV), a widespread opportunistic pathogen. This network
contains all known interactions and functional modules (i.e. groups of
proteins) coordinately responding to HCMV entry. The number of both genes and
functional modules activated in this network dramatically declines shortly,
within 25 min post-infection. While modules annotated as receptor system, ion
transport, and immune response are continuously activated during the entire
process of HCMV entry, those for cell adhesion and skeletal movement are
specifically activated during viral early attachment, and those for immune
response during virus entry. HCMV entry requires a complex receptor network
involving different cellular components, comprising not only cell surface
receptors, but also pathway components in signal transduction, skeletal
development, immune response, endocytosis, ion transport, macromolecule
metabolism and chromatin remodeling. Interestingly, genes that function in
chromatin remodeling are the most abundant in this receptor system, suggesting
that global modulation of transcriptions is one of the most important events in
HCMV entry. Results of in silico knock out further reveal that this entire
receptor network is primarily controlled by multiple elements, such as EGFR
(Epidermal Growth Factor) and SLC10A1 (sodium/bile acid cotransporter family,
member 1). Thus, our results demonstrate that a complex systemic network, in
which components coordinating efficiently in time and space contributes to
virus entry.Comment: 26 page
Distributed Training Large-Scale Deep Architectures
Scale of data and scale of computation infrastructures together enable the
current deep learning renaissance. However, training large-scale deep
architectures demands both algorithmic improvement and careful system
configuration. In this paper, we focus on employing the system approach to
speed up large-scale training. Via lessons learned from our routine
benchmarking effort, we first identify bottlenecks and overheads that hinter
data parallelism. We then devise guidelines that help practitioners to
configure an effective system and fine-tune parameters to achieve desired
speedup. Specifically, we develop a procedure for setting minibatch size and
choosing computation algorithms. We also derive lemmas for determining the
quantity of key components such as the number of GPUs and parameter servers.
Experiments and examples show that these guidelines help effectively speed up
large-scale deep learning training
Optimal Resource Allocation in Random Networks with Transportation Bandwidths
We apply statistical physics to study the task of resource allocation in
random sparse networks with limited bandwidths for the transportation of
resources along the links. Useful algorithms are obtained from recursive
relations. Bottlenecks emerge when the bandwidths are small, causing an
increase in the fraction of idle links. For a given total bandwidth per node,
the efficiency of allocation increases with the network connectivity. In the
high connectivity limit, we find a phase transition at a critical bandwidth,
above which clusters of balanced nodes appear, characterised by a profile of
homogenized resource allocation similar to the Maxwell's construction.Comment: 28 pages, 11 figure
Impact of community structure on information transfer
The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount
Scaling readiness: Concepts, practices, and implementation.
Scaling Readiness is an approach that can support organizations, projects, and programs in achieving their ambitions to scale innovations and achieve impact. Scaling Readiness encourages critical reflection on how ready innovations are for scaling, and what appropriate actions could accelerate or enhance scaling
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