53,382 research outputs found
Discrete-Time Chaotic-Map Truly Random Number Generators: Design, Implementation, and Variability Analysis of the Zigzag Map
In this paper, we introduce a novel discrete chaotic map named zigzag map
that demonstrates excellent chaotic behaviors and can be utilized in Truly
Random Number Generators (TRNGs). We comprehensively investigate the map and
explore its critical chaotic characteristics and parameters. We further present
two circuit implementations for the zigzag map based on the switched current
technique as well as the current-mode affine interpolation of the breakpoints.
In practice, implementation variations can deteriorate the quality of the
output sequence as a result of variation of the chaotic map parameters. In
order to quantify the impact of variations on the map performance, we model the
variations using a combination of theoretical analysis and Monte-Carlo
simulations on the circuits. We demonstrate that even in the presence of the
map variations, a TRNG based on the zigzag map passes all of the NIST 800-22
statistical randomness tests using simple post processing of the output data.Comment: To appear in Analog Integrated Circuits and Signal Processing (ALOG
Stochastic lattice models for the dynamics of linear polymers
Linear polymers are represented as chains of hopping reptons and their motion
is described as a stochastic process on a lattice. This admittedly crude
approximation still catches essential physics of polymer motion, i.e. the
universal properties as function of polymer length. More than the static
properties, the dynamics depends on the rules of motion. Small changes in the
hopping probabilities can result in different universal behavior. In particular
the cross-over between Rouse dynamics and reptation is controlled by the types
and strength of the hoppings that are allowed. The properties are analyzed
using a calculational scheme based on an analogy with one-dimensional spin
systems. It leads to accurate data for intermediately long polymers. These are
extrapolated to arbitrarily long polymers, by means of finite-size-scaling
analysis. Exponents and cross-over functions for the renewal time and the
diffusion coefficient are discussed for various types of motion.Comment: 60 pages, 19 figure
Machine learning for crystal identification and discovery
As computers get faster, researchers -- not hardware or algorithms -- become
the bottleneck in scientific discovery. Computational study of colloidal
self-assembly is one area that is keenly affected: even after computers
generate massive amounts of raw data, performing an exhaustive search to
determine what (if any) ordered structures occur in a large parameter space of
many simulations can be excruciating. We demonstrate how machine learning can
be applied to discover interesting areas of parameter space in colloidal self
assembly. We create numerical fingerprints -- inspired by bond orientational
order diagrams -- of structures found in self-assembly studies and use these
descriptors to both find interesting regions in a phase diagram and identify
characteristic local environments in simulations in an automated manner for
simple and complex crystal structures. Utilizing these methods allows analysis
methods to keep up with the data generation ability of modern high-throughput
computing environments.Comment: Fixed typo, added missing acknowledgment, added supplementary
informatio
Simulation of 1+1 dimensional surface growth and lattices gases using GPUs
Restricted solid on solid surface growth models can be mapped onto binary
lattice gases. We show that efficient simulation algorithms can be realized on
GPUs either by CUDA or by OpenCL programming. We consider a
deposition/evaporation model following Kardar-Parisi-Zhang growth in 1+1
dimensions related to the Asymmetric Simple Exclusion Process and show that for
sizes, that fit into the shared memory of GPUs one can achieve the maximum
parallelization speedup ~ x100 for a Quadro FX 5800 graphics card with respect
to a single CPU of 2.67 GHz). This permits us to study the effect of quenched
columnar disorder, requiring extremely long simulation times. We compare the
CUDA realization with an OpenCL implementation designed for processor clusters
via MPI. A two-lane traffic model with randomized turning points is also
realized and the dynamical behavior has been investigated.Comment: 20 pages 12 figures, 1 table, to appear in Comp. Phys. Com
BarrierPoint: sampled simulation of multi-threaded applications
Sampling is a well-known technique to speed up architectural simulation of long-running workloads while maintaining accurate performance predictions. A number of sampling techniques have recently been developed that extend well- known single-threaded techniques to allow sampled simulation of multi-threaded applications. Unfortunately, prior work is limited to non-synchronizing applications (e.g., server throughput workloads); requires the functional simulation of the entire application using a detailed cache hierarchy which limits the overall simulation speedup potential; leads to different units of work across different processor architectures which complicates performance analysis; or, requires massive machine resources to achieve reasonable simulation speedups. In this work, we propose BarrierPoint, a sampling methodology to accelerate simulation by leveraging globally synchronizing barriers in multi-threaded applications. BarrierPoint collects microarchitecture-independent code and data signatures to determine the most representative inter-barrier regions, called barrierpoints. BarrierPoint estimates total application execution time (and other performance metrics of interest) through detailed simulation of these barrierpoints only, leading to substantial simulation speedups. Barrierpoints can be simulated in parallel, use fewer simulation resources, and define fixed units of work to be used in performance comparisons across processor architectures. Our evaluation of BarrierPoint using NPB and Parsec benchmarks reports average simulation speedups of 24.7x (and up to 866.6x) with an average simulation error of 0.9% and 2.9% at most. On average, BarrierPoint reduces the number of simulation machine resources needed by 78x
Application of Hierarchical Matrix Techniques To The Homogenization of Composite Materials
In this paper, we study numerical homogenization methods based on integral
equations. Our work is motivated by materials such as concrete, modeled as
composites structured as randomly distributed inclusions imbedded in a matrix.
We investigate two integral reformulations of the corrector problem to be
solved, namely the equivalent inclusion method based on the Lippmann-Schwinger
equation, and a method based on boundary integral equations. The fully
populated matrices obtained by the discretization of the integral operators are
successfully dealt with using the H-matrix format
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