30,851 research outputs found
Hybrid-control of synapse circuits for programmable cellular neural networks
This paper describes a hybrid weight-control strategy for VLSI realizations of programmable Cellular Neural Networks (CNNs), based on auto-tuning of analog control signals to digitally specified values. The approach merges the advantages of digital and analog programmability, achieving low areas and reduced number of control lines, simplifying the control and storage of weight values, and eliminating their dependency on global process-parameter variations
Design of a Hybrid Modular Switch
Network Function Virtualization (NFV) shed new light for the design,
deployment, and management of cloud networks. Many network functions such as
firewalls, load balancers, and intrusion detection systems can be virtualized
by servers. However, network operators often have to sacrifice programmability
in order to achieve high throughput, especially at networks' edge where complex
network functions are required.
Here, we design, implement, and evaluate Hybrid Modular Switch (HyMoS). The
hybrid hardware/software switch is designed to meet requirements for modern-day
NFV applications in providing high-throughput, with a high degree of
programmability. HyMoS utilizes P4-compatible Network Interface Cards (NICs),
PCI Express interface and CPU to act as line cards, switch fabric, and fabric
controller respectively. In our implementation of HyMos, PCI Express interface
is turned into a non-blocking switch fabric with a throughput of hundreds of
Gigabits per second.
Compared to existing NFV infrastructure, HyMoS offers modularity in hardware
and software as well as a higher degree of programmability by supporting a
superset of P4 language
Programmable models of growth and mutation of cancer-cell populations
In this paper we propose a systematic approach to construct mathematical
models describing populations of cancer-cells at different stages of disease
development. The methodology we propose is based on stochastic Concurrent
Constraint Programming, a flexible stochastic modelling language. The
methodology is tested on (and partially motivated by) the study of prostate
cancer. In particular, we prove how our method is suitable to systematically
reconstruct different mathematical models of prostate cancer growth - together
with interactions with different kinds of hormone therapy - at different levels
of refinement.Comment: In Proceedings CompMod 2011, arXiv:1109.104
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Pseudorandom number generation with self programmable cellular automata
In this paper, we propose a new class of cellular automata – self programming cellular automata (SPCA) with specific application to pseudorandom number generation. By changing a cell's state transition rules in relation to factors such as its neighboring cell's states, behavioral complexity can be increased and utilized. Interplay between the state transition neighborhood and rule selection neighborhood leads to a new composite neighborhood and state transition rule that is the linear combination of two different mappings with different temporal dependencies. It is proved that when the transitional matrices for both the state transition and rule selection neighborhood are non-singular, SPCA will not exhibit non-group behavior. Good performance can be obtained using simple neighborhoods with certain CA length, transition rules etc. Certain configurations of SPCA pass all DIEHARD and ENT tests with an implementation cost lower than current reported work. Output sampling methods are also suggested to improve output efficiency by sampling the outputs of the new rule selection neighborhoods
Quantum Processors and Controllers
In this paper is presented an abstract theory of quantum processors and
controllers, special kind of quantum computational network defined on a
composite quantum system with two parts: the controlling and controlled
subsystems. Such approach formally differs from consideration of quantum
control as some external influence on a system using some set of Hamiltonians
or quantum gates. The model of programmed quantum controllers discussed in
present paper is based on theory of universal deterministic quantum processors
(programmable gate arrays). Such quantum devices may simulate arbitrary
evolution of quantum system and so demonstrate an example of universal quantum
control.
Keywords: Quantum, Computer, Control, Processor, UniversalComment: LaTeXe, 7 pp, 2 col, v3: revised and extended (+50%), PhysCon0
Building Programmable Wireless Networks: An Architectural Survey
In recent times, there have been a lot of efforts for improving the ossified
Internet architecture in a bid to sustain unstinted growth and innovation. A
major reason for the perceived architectural ossification is the lack of
ability to program the network as a system. This situation has resulted partly
from historical decisions in the original Internet design which emphasized
decentralized network operations through co-located data and control planes on
each network device. The situation for wireless networks is no different
resulting in a lot of complexity and a plethora of largely incompatible
wireless technologies. The emergence of "programmable wireless networks", that
allow greater flexibility, ease of management and configurability, is a step in
the right direction to overcome the aforementioned shortcomings of the wireless
networks. In this paper, we provide a broad overview of the architectures
proposed in literature for building programmable wireless networks focusing
primarily on three popular techniques, i.e., software defined networks,
cognitive radio networks, and virtualized networks. This survey is a
self-contained tutorial on these techniques and its applications. We also
discuss the opportunities and challenges in building next-generation
programmable wireless networks and identify open research issues and future
research directions.Comment: 19 page
Optimal analog wavelet bases construction using hybrid optimization algorithm
An approach for the construction of optimal analog wavelet bases is presented. First, the definition of an analog wavelet is given. Based on the definition and the least-squares error criterion, a general framework for designing optimal analog wavelet bases is established, which is one of difficult nonlinear constrained optimization problems. Then, to solve this problem, a hybrid algorithm by combining chaotic map particle swarm optimization (CPSO) with local sequential quadratic programming (SQP) is proposed. CPSO is an improved PSO in which the saw tooth chaotic map is used to raise its global search ability. CPSO is a global optimizer to search the estimates of the global solution, while the SQP is employed for the local search and refining the estimates. Benefiting from good global search ability of CPSO and powerful local search ability of SQP, a high-precision global optimum in this problem can be gained. Finally, a series of optimal analog wavelet bases are constructed using the hybrid algorithm. The proposed method is tested for various wavelet bases and the improved performance is compared with previous works.Peer reviewedFinal Published versio
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