57,496 research outputs found
OutFlank Routing: Increasing Throughput in Toroidal Interconnection Networks
We present a new, deadlock-free, routing scheme for toroidal interconnection
networks, called OutFlank Routing (OFR). OFR is an adaptive strategy which
exploits non-minimal links, both in the source and in the destination nodes.
When minimal links are congested, OFR deroutes packets to carefully chosen
intermediate destinations, in order to obtain travel paths which are only an
additive constant longer than the shortest ones. Since routing performance is
very sensitive to changes in the traffic model or in the router parameters, an
accurate discrete-event simulator of the toroidal network has been developed to
empirically validate OFR, by comparing it against other relevant routing
strategies, over a range of typical real-world traffic patterns. On the
16x16x16 (4096 nodes) simulated network OFR exhibits improvements of the
maximum sustained throughput between 14% and 114%, with respect to Adaptive
Bubble Routing.Comment: 9 pages, 5 figures, to be presented at ICPADS 201
Ethernet - a survey on its fields of application
During the last decades, Ethernet progressively became the most widely used local area networking (LAN) technology. Apart from LAN installations, Ethernet became also attractive for many other fields of application, ranging from industry to avionics, telecommunication, and multimedia. The expanded application of this technology is mainly due to its significant assets like reduced cost, backward-compatibility, flexibility, and expandability. However, this new trend raises some problems concerning the services of the protocol and the requirements for each application. Therefore, specific adaptations prove essential to integrate this communication technology in each field of application. Our primary objective is to show how Ethernet has been enhanced to comply with the specific requirements of several application fields, particularly in transport, embedded and multimedia contexts. The paper first describes the common Ethernet LAN technology and highlights its main features. It reviews the most important specific Ethernet versions with respect to each application fieldâs requirements. Finally, we compare these different fields of application and we particularly focus on the fundamental concepts and the quality of service capabilities of each proposal
A Survey of Green Networking Research
Reduction of unnecessary energy consumption is becoming a major concern in
wired networking, because of the potential economical benefits and of its
expected environmental impact. These issues, usually referred to as "green
networking", relate to embedding energy-awareness in the design, in the devices
and in the protocols of networks. In this work, we first formulate a more
precise definition of the "green" attribute. We furthermore identify a few
paradigms that are the key enablers of energy-aware networking research. We
then overview the current state of the art and provide a taxonomy of the
relevant work, with a special focus on wired networking. At a high level, we
identify four branches of green networking research that stem from different
observations on the root causes of energy waste, namely (i) Adaptive Link Rate,
(ii) Interface proxying, (iii) Energy-aware infrastructures and (iv)
Energy-aware applications. In this work, we do not only explore specific
proposals pertaining to each of the above branches, but also offer a
perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate;
Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications.
18 pages, 6 figures, 2 table
Pulling Out All the Tops with Computer Vision and Deep Learning
We apply computer vision with deep learning -- in the form of a convolutional
neural network (CNN) -- to build a highly effective boosted top tagger.
Previous work (the "DeepTop" tagger of Kasieczka et al) has shown that a
CNN-based top tagger can achieve comparable performance to state-of-the-art
conventional top taggers based on high-level inputs. Here, we introduce a
number of improvements to the DeepTop tagger, including architecture, training,
image preprocessing, sample size and color pixels. Our final CNN top tagger
outperforms BDTs based on high-level inputs by a factor of --3 or more
in background rejection, over a wide range of tagging efficiencies and fiducial
jet selections. As reference points, we achieve a QCD background rejection
factor of 500 (60) at 50\% top tagging efficiency for fully-merged (non-merged)
top jets with in the 800--900 GeV (350--450 GeV) range. Our CNN can also
be straightforwardly extended to the classification of other types of jets, and
the lessons learned here may be useful to others designing their own deep NNs
for LHC applications.Comment: 33 pages, 11 figure
Reconfigurable interconnects in DSM systems: a focus on context switch behavior
Recent advances in the development of reconfigurable optical interconnect technologies allow for the fabrication of low cost and run-time adaptable interconnects in large distributed shared-memory (DSM) multiprocessor machines. This can allow the use of adaptable interconnection networks that alleviate the huge bottleneck present due to the gap between the processing speed and the memory access time over the network. In this paper we have studied the scheduling of tasks by the kernel of the operating system (OS) and its influence on communication between the processing nodes of the system, focusing on the traffic generated just after a context switch. We aim to use these results as a basis to propose a potential reconfiguration of the network that could provide a significant speedup
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