145,874 research outputs found
Algorithms and Throughput Analysis for MDS-Coded Switches
Network switches and routers need to serve packet writes and reads at rates
that challenge the most advanced memory technologies. As a result, scaling the
switching rates is commonly done by parallelizing the packet I/Os using
multiple memory units. For improved read rates, packets can be coded with an
[n,k] MDS code, thus giving more flexibility at read time to achieve higher
utilization of the memory units. In the paper, we study the usage of [n,k] MDS
codes in a switching environment. In particular, we study the algorithmic
problem of maximizing the instantaneous read rate given a set of packet
requests and the current layout of the coded packets in memory. The most
interesting results from practical standpoint show how the complexity of
reaching optimal read rate depends strongly on the writing policy of the coded
packets.Comment: 6 pages, an extended version of a paper accepted to the 2015 IEEE
International Symposium on Information Theory (ISIT
Competitive Advantage for Multiple-Memory Strategies in an Artificial Market
We consider a simple binary market model containing competitive agents.
The novel feature of our model is that it incorporates the tendency shown by
traders to look for patterns in past price movements over multiple time scales,
i.e. {\em multiple memory-lengths}. In the regime where these memory-lengths
are all small, the average winnings per agent exceed those obtained for either
(1) a pure population where all agents have equal memory-length, or (2) a mixed
population comprising sub-populations of equal-memory agents with each
sub-population having a different memory-length. Agents who consistently play
strategies of a given memory-length, are found to win more on average --
switching between strategies with different memory lengths incurs an effective
penalty, while switching between strategies of equal memory does not. Agents
employing short-memory strategies can outperform agents using long-memory
strategies, even in the regime where an equal-memory system would have favored
the use of long-memory strategies. Using the many-body `Crowd-Anticrowd'
theory, we obtain analytic expressions which are in good agreement with the
observed numerical results. In the context of financial markets, our results
suggest that multiple-memory agents have a better chance of identifying price
patterns of unknown length and hence will typically have higher winnings.Comment: Talk to be given at the SPIE conference on Econophysics and Finance,
in the International Symposium 'Fluctuations and Noise', 23-26 May 2005 in
Austin, Texa
A status update on the determination of by the ALPHA collaboration
The ALPHA collaboration aims to determine with a total error
below the percent level. A further step towards this goal can be taken by
combining results from the recent simulations of 2+1-flavour QCD by the CLS
initiative with a number of tools developed over the years: renormalized
couplings in finite volume schemes, recursive finite size techniques, two-loop
renormalized perturbation theory and the (improved) gradient flow on the
lattice. We sketch the strategy, which involves both the standard SF coupling
in the high energy regime and a gradient flow coupling at low energies. This
implies the need for matching both schemes at an intermediate switching scale,
, which we choose roughly in the range 2-4 GeV. In this
contribution we present a preliminary result for this matching procedure, and
we then focus on our almost final results for the scale evolution of the SF
coupling from towards the perturbative regime, where we extract
the -parameter, , in units of . Connecting and
thus the -parameter to a hadronic scale such as requires 2
further ingredients: first, the connection of to
using a few steps with the step-scaling function of the gradient flow coupling,
and, second, the continuum extrapolation of .Comment: 7 pages, 4 figures, Proceedings of the 33rd International Symposium
on Lattice Field Theory (Lattice 2015), 14-18 July 2015, Kobe, Japa
Improved Pseudorandom Generators from Pseudorandom Multi-Switching Lemmas
We give the best known pseudorandom generators for two touchstone classes in
unconditional derandomization: an -PRG for the class of size-
depth- circuits with seed length , and an -PRG for the class of -sparse
polynomials with seed length . These results bring the state of the art for
unconditional derandomization of these classes into sharp alignment with the
state of the art for computational hardness for all parameter settings:
improving on the seed lengths of either PRG would require breakthrough progress
on longstanding and notorious circuit lower bounds.
The key enabling ingredient in our approach is a new \emph{pseudorandom
multi-switching lemma}. We derandomize recently-developed
\emph{multi}-switching lemmas, which are powerful generalizations of
H{\aa}stad's switching lemma that deal with \emph{families} of depth-two
circuits. Our pseudorandom multi-switching lemma---a randomness-efficient
algorithm for sampling restrictions that simultaneously simplify all circuits
in a family---achieves the parameters obtained by the (full randomness)
multi-switching lemmas of Impagliazzo, Matthews, and Paturi [IMP12] and
H{\aa}stad [H{\aa}s14]. This optimality of our derandomization translates into
the optimality (given current circuit lower bounds) of our PRGs for
and sparse polynomials
Robust Model Predictive Longitudinal Position Tracking Control for an Autonomous Vehicle Based on Multiple Models
The aim of this work is to control the longitudinal position of an autonomous
vehicle with an internal combustion engine. The powertrain has an inherent
dead-time characteristic and constraints on physical states apply since the
vehicle is neither able to accelerate arbitrarily strong, nor to drive
arbitrarily fast. A model predictive controller (MPC) is able to cope with both
of the aforementioned system properties. MPC heavily relies on a model and
therefore a strategy on how to obtain multiple linear state space prediction
models of the nonlinear system via input/output data system identification from
acceleration data is given. The models are identified in different regions of
the vehicle dynamics in order to obtain more accurate predictions. The still
remaining plant-model mismatch can be expressed as an additive disturbance
which can be handled through robust control theory. Therefore modifications to
the models for applying robust MPC tracking control theory are described. Then
a controller which guarantees robust constraint satisfaction and recursive
feasibility is designed. As a next step, modifications to apply the controller
on multiple models are discussed. In this context, a model switching strategy
is provided and theoretical and computational limitations are pointed out.
Lastly, simulation results are presented and discussed, including computational
load when switching between systems.Comment: Accepted for 2020 IEEE Symposium Series on Computational Intelligence
(IEEE SSCI
Non-Malleable Codes for Small-Depth Circuits
We construct efficient, unconditional non-malleable codes that are secure
against tampering functions computed by small-depth circuits. For
constant-depth circuits of polynomial size (i.e. tampering
functions), our codes have codeword length for a -bit
message. This is an exponential improvement of the previous best construction
due to Chattopadhyay and Li (STOC 2017), which had codeword length
. Our construction remains efficient for circuit depths as
large as (indeed, our codeword length remains
, and extending our result beyond this would require
separating from .
We obtain our codes via a new efficient non-malleable reduction from
small-depth tampering to split-state tampering. A novel aspect of our work is
the incorporation of techniques from unconditional derandomization into the
framework of non-malleable reductions. In particular, a key ingredient in our
analysis is a recent pseudorandom switching lemma of Trevisan and Xue (CCC
2013), a derandomization of the influential switching lemma from circuit
complexity; the randomness-efficiency of this switching lemma translates into
the rate-efficiency of our codes via our non-malleable reduction.Comment: 26 pages, 4 figure
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