43,802 research outputs found
Fast, accurate and flexible data locality analysis
This paper presents a tool based on a new approach for analyzing the locality exhibited by data memory references. The tool is very fast because it is based on a static locality analysis enhanced with very simple profiling information, which results in a negligible slowdown. This feature allows the tool to be used for highly time-consuming applications and to include it as a step in a typical iterative analysis-optimization process. The tool can provide a detailed evaluation of the reuse exhibited by a program, quantifying and qualifying the different types of misses either globally or detailed by program sections, data structures, memory instructions, etc. The accuracy of the tool is validated by comparing its results with those provided by a simulator.Peer ReviewedPostprint (published version
Learning to Navigate the Energy Landscape
In this paper, we present a novel and efficient architecture for addressing
computer vision problems that use `Analysis by Synthesis'. Analysis by
synthesis involves the minimization of the reconstruction error which is
typically a non-convex function of the latent target variables.
State-of-the-art methods adopt a hybrid scheme where discriminatively trained
predictors like Random Forests or Convolutional Neural Networks are used to
initialize local search algorithms. While these methods have been shown to
produce promising results, they often get stuck in local optima. Our method
goes beyond the conventional hybrid architecture by not only proposing multiple
accurate initial solutions but by also defining a navigational structure over
the solution space that can be used for extremely efficient gradient-free local
search. We demonstrate the efficacy of our approach on the challenging problem
of RGB Camera Relocalization. To make the RGB camera relocalization problem
particularly challenging, we introduce a new dataset of 3D environments which
are significantly larger than those found in other publicly-available datasets.
Our experiments reveal that the proposed method is able to achieve
state-of-the-art camera relocalization results. We also demonstrate the
generalizability of our approach on Hand Pose Estimation and Image Retrieval
tasks
Elastic properties of proteins: insight on the folding process and evolutionary selection of native structures
We carry out a theoretical study of the vibrational and relaxation properties
of naturally-occurring proteins with the purpose of characterizing both the
folding and equilibrium thermodynamics. By means of a suitable model we provide
a full characterization of the spectrum and eigenmodes of vibration at various
temperatures by merely exploiting the knowledge of the protein native
structure. It is shown that the rate at which perturbations decay at the
folding transition correlates well with experimental folding rates. This
validation is carried out on a list of about 30 two-state folders. Furthermore,
the qualitative analysis of residues mean square displacements (shown to
accurately reproduce crystallographic data) provides a reliable and
statistically accurate method to identify crucial folding sites/contacts. This
novel strategy is validated against clinical data for HIV-1 Protease. Finally,
we compare the spectra and eigenmodes of vibration of natural proteins against
randomly-generated compact structures and regular random graphs. The comparison
reveals a distinctive enhanced flexibility of natural structures accompanied by
slow relaxation times at the folding temperature. The fact that these
properties are intimately connected to the presence and assembly of secondary
motifs hints at the special criteria adopted by evolution in the selection of
viable folds.Comment: Revtex 17 pages, 13 eps figure
Unravelling the Impact of Temporal and Geographical Locality in Content Caching Systems
To assess the performance of caching systems, the definition of a proper
process describing the content requests generated by users is required.
Starting from the analysis of traces of YouTube video requests collected inside
operational networks, we identify the characteristics of real traffic that need
to be represented and those that instead can be safely neglected. Based on our
observations, we introduce a simple, parsimonious traffic model, named Shot
Noise Model (SNM), that allows us to capture temporal and geographical locality
of content popularity. The SNM is sufficiently simple to be effectively
employed in both analytical and scalable simulative studies of caching systems.
We demonstrate this by analytically characterizing the performance of the LRU
caching policy under the SNM, for both a single cache and a network of caches.
With respect to the standard Independent Reference Model (IRM), some
paradigmatic shifts, concerning the impact of various traffic characteristics
on cache performance, clearly emerge from our results.Comment: 14 pages, 11 Figures, 2 Appendice
A Comparison of Blocking Methods for Record Linkage
Record linkage seeks to merge databases and to remove duplicates when unique
identifiers are not available. Most approaches use blocking techniques to
reduce the computational complexity associated with record linkage. We review
traditional blocking techniques, which typically partition the records
according to a set of field attributes, and consider two variants of a method
known as locality sensitive hashing, sometimes referred to as "private
blocking." We compare these approaches in terms of their recall, reduction
ratio, and computational complexity. We evaluate these methods using different
synthetic datafiles and conclude with a discussion of privacy-related issues.Comment: 22 pages, 2 tables, 7 figure
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