arXiv subjects

Leo Ferres

Publications and source records attributed to Leo Ferres.

23 records · Page 2Linked to original sources

arXiv2017

The Effect of Pokémon Go on The Pulse of the City: A Natural Experiment

Pokémon Go, a location-based game that uses augmented reality techniques, received unprecedented media coverage due to claims that it allowed for greater access to public spaces, increasing the number of people out on the streets, and generally improving health, social, and security indices. However, the true impact of Pokémon Go on people's mobility patterns in a city is still largely unknown. In this paper, we perform a natural experiment using data from mobile phone networks to evaluate the effect of Pokémon Go on the pulse of a big city: Santiago, capital of Chile. We found significant effects of the game on the floating population of Santiago compared to movement prior to the game's release in August 2016: in the following week, up to 13.8\% more people spent time outside at certain times of the day, even if they do not seem to go out of their usual way. These effects were found by performing regressions using count models over the states of the cellphone network during each day under study. The models used controlled for land use, daily patterns, and points of interest in the city. Our results indicate that, on business days, there are more people on the street at commuting times, meaning that people did not change their daily routines but slightly adapted them to play the game. Conversely, on Saturday and Sunday night, people indeed went out to play, but favored places close to where they live. Even if the statistical effects of the game do not reflect the massive change in mobility behavior portrayed by the media, at least in terms of expanse, they do show how "the street" may become a new place of leisure. This change should have an impact on long-term infrastructure investment by city officials, and on the drafting of public policies aimed at stimulating pedestrian traffic.

cs.SI↗

arXiv2017

Parallel Construction of Compact Planar Embeddings

The sheer sizes of modern datasets are forcing data-structure designers to consider seriously both parallel construction and compactness. To achieve those goals we need to design a parallel algorithm with good scalability and with low memory consumption. An algorithm with good scalability improves its performance when the number of available cores increases, and an algorithm with low memory consumption uses memory proportional to the space used by the dataset in uncompact form. In this work, we discuss the engineering of a parallel algorithm with linear work and logarithmic span for the construction of the compact representation of planar embeddings. We also provide an experimental study of our implementation and prove experimentally that it has good scalability and low memory consumption. Additionally, we describe and test experimentally queries supported by the compact representation.

cs.DS↗

arXiv2016

Parallel Construction of Wavelet Trees on Multicore Architectures

The wavelet tree has become a very useful data structure to efficiently represent and query large volumes of data in many different domains, from bioinformatics to geographic information systems. One problem with wavelet trees is their construction time. In this paper, we introduce two algorithms that reduce the time complexity of a wavelet tree's construction by taking advantage of nowadays ubiquitous multicore machines. Our first algorithm constructs all the levels of the wavelet in parallel in $O(n)$ time and $O(n\lgσ+ σ\lg n)$ bits of working space, where $n$ is the size of the input sequence and $σ$ is the size of the alphabet. Our second algorithm constructs the wavelet tree in a domain-decomposition fashion, using our first algorithm in each segment, reaching $O(\lg n)$ time and $O(n\lgσ+ pσ\lg n/\lgσ)$ bits of extra space, where $p$ is the number of available cores. Both algorithms are practical and report good speedup for large real datasets.

cs.DS↗

arXiv2016

Empirical Evaluation of a Thread-Safe Dynamic Range Min-Max Tree using HTM

Succinct trees, such as wavelet trees and those based on, for instance, range Min-Max trees (RMMTs), are a family of practical data structures that store information close to their information-theoretic space lower bound. These structures are often static; meaning that once they are built, nodes cannot be added, deleted or modified. This read-only property simplifies concurrency. However, newer versions of these data structures allow for a fair degree of dynamism. Parallel programming using Hardware Transactional Memory(HTM), has been available in mainstream microprocessors since a few years ago. One limitation of HTM is still on the size of each transaction. This is why HTM's use, for the moment, is limited to operations that involve few memory addresses that need to be updated atomically, or where the level of concurrency is low. We provide the first available implementation of a concurrent, dynamic RMMT based on HTM, and we compare empirically how well HTM performs compared to a naive implementation using locks. We have shown that because of the formal properties of RMMTs, HTM is a good fit for adding concurrency to otherwise slow lock-based alternatives. We have also shown that HTM performs better than locks when the number of write operations increase, making it a practical structure to use in several write-intensive contexts. This is, as far as we know, the only practical implementation of RMMTs thoroughly tested using HTM.

cs.DC↗

arXiv2013

Cache Performance Study of Portfolio-Based Parallel CDCL SAT Solvers

Parallel SAT solvers are becoming mainstream. Their performance has made them win the past two SAT competitions consecutively and are in the limelight of research and industry. The problem is that it is not known exactly what is needed to make them perform even better; that is, how to make them solve more problems in less time. Also, it is also not know how well they scale in massive multi-core environments which, predictably, is the scenario of comming new hardware. In this paper we show that cache contention is a main culprit of a slowing down in scalability, and provide empirical results that for some type of searches, physically sharing the clause Database between threads is beneficial.

cs.DC↗