pinecone/core-2020-05-10-deduplication huggingface dataset:
Multifrontal QR Factorization for Multicore Architectures over Runtime Systems

To face the advent of multicore processors and the ever increasing complexity of hardware architectures, programming models based on DAG parallelism regained popularity in the high performance, scientific computing community. Modern runtime systems offer a programming interface that complies with this paradigm and powerful engines for scheduling the tasks into which the application is decomposed. These tools have already proved their effectiveness on a number of dense linear algebra applications. This paper evaluates the usability of runtime systems for complex applications, namely, sparse matrix multifrontal factorizations which constitute extremely irregular workloads, with tasks of different granularities and characteristics and with a variable memory consumption. Experimental results on real-life matrices show that it is possible to achieve the same efficiency as with an ad hoc scheduler which relies on the knowledge of the algorithm. A detailed analysis shows the performance behavior of the resulting code and possible ways of improving the effectiveness of runtime systems
Dynamic Thread Pinning for Phase-Based OpenMP Programs

F. Wolf, B. Mohr, and D. an Ney (Eds.), pages 12, pp. 53-64International audienceThread affinity has appeared as an important technique to improve the overall program performance and for better performance stability. However, if we consider a program with multiple phases, it is unlikely that a single thread affinity produces the best program performance for all these phases. If we consider the case of OpenMP, applications may have multiple parallel regions, each with a distinct inter-thread data sharing pattern. In this paper, we propose an approach that allows to change thread affinity dynamically (thread migrations) between parallel regions at runtime to account for these distinct inter-thread data sharing patterns. We demonstrate that as far as cache sharing is concerned for SPEC OMP01, not all the tested OpenMP applications exhibit a distinct phase behavior. However, we show that while fixing thread affinity for the whole execution may improve performance by up to 30%, allowing dynamic thread pinning may improve performance by up to 40%. Furthermore, we provide an analysis about the required conditions to improve the effectiveness of the approac
GPU accelerated maximum cardinality matching algorithms for bipartite graphs

International audienceWe design, implement, and evaluate GPU-based algorithms for the maximum cardinality matching problem in bipartite graphs. Such algorithms have a variety of applications in computer science, scientific computing, bioinformatics, and other areas. To the best of our knowledge, ours is the first study which focuses on the GPU implementation of the maximum cardinality matching algorithms. We compare the proposed algorithms with serial and multicore implementations from the literature on a large set of real-life problems where in majority of the cases one of our GPU-accelerated algorithms is demonstrated to be faster than both the sequential and multicore implementations
Data Partitioning for Minimizing Transferred Data in MapReduce

International audienceReducing data transfer in MapReduce's shuffle phase is very important because it increases data locality of reduce tasks, and thus decreases the overhead of job executions. In the literature, several optimizations have been proposed to reduce data transfer between mappers and reducers. Nevertheless, all these approaches are limited by how intermediate key-value pairs are distributed over map outputs. In this paper, we address the problem of high data transfers in MapReduce, and propose a technique that repartitions tuples of the input datasets, and thereby optimizes the distribution of key-values over mappers, and increases the data locality in reduce tasks. Our approach captures the relationships between input tuples and intermediate keys by monitoring the execution of a set of MapReduce jobs which are representative of the workload. Then, based on those relationships, it assigns input tuples to the appropriate chunks. We evaluated our approach through experimentation in a Hadoop deployment on top of Grid5000 using standard benchmarks. The results show high reduction in data transfer during the shuffle phase compared to Native Hadoop
Repair Time in Distributed Storage Systems

International audienceIn this paper, we analyze a highly distributed backup stor- age system realized by means of nano datacenters (NaDa). NaDa have been recently proposed as a way to mitigate the growing energy, band- width and device costs of traditional data centers, following the popu- larity of cloud computing. These service provider-controlled peer-to-peer systems take advantage of resources already committed to always-on set top boxes, the fact they do not generate heat dissipation costs and their proximity to users. In this kind of systems redundancy is introduced to preserve the data in case of peer failures or departures. To ensure long-term fault tolerance, the storage system must have a self-repairing service that continuously reconstructs the fragments of redundancy that are lost. The speed of this reconstruction process is crucial for the data survival. This speed is mainly determined by how much bandwidth, which is a critical re- source of such systems, is available. In the literature, the reconstruc- tion times are modeled as independent (e.g., poissonian, deterministic, or more generally following any distribution). In practice, however, nu- merous reconstructions start at the same time (when the system detects that a peer has failed). Consequently, they are correlated to each other because concurrent reconstructions do compete for the same bandwidth. This correlation negatively impacts the efficiency of the bandwidth uti- lization and henceforth the repair time. We propose a new analytical framework that takes into account this correlation when estimating the repair time and the probability of data loss. Mainly, we introduce a queuing model in which reconstructions are served by peers at a rate that depends on the available bandwidth. We show that the load is unbalanced among peers (young peers inherently store less data than the old ones). This leads us to introduce a correcting factor on the repair rate of the system. The models and schemes proposed are validated by mathematical analysis, extensive set of simulations, and experimentation using the GRID5000 test-bed platform. This new model allows system designers to operate a more accurate choice of system parameters in function of their targeted data durability
As-Soon-As-Possible Top-k Query Processing in P2P Systems

International audienceTop-k query processing techniques provide two main advantages for unstructured peer-to-peer (P2P) systems. First they avoid overwhelming users with too many results. Second they reduce significantly network resources consumption. However, existing approaches suffer from long waiting times. This is because top-k results are returned only when all queried peers have finished processing the query. As a result, query response time is dominated by the slowest queried peer. In this paper, we address this users' waiting time problem. For this, we revisit top-k query processing in P2P systems by introducing two novel notions in addition to response time: the stabilization time and the cumulative quality gap. Using these notions, we formally define the as-soonas-possible (ASAP) top-k processing problem. Then, we propose a family of algorithms called ASAP to deal with this problem. We validate our solution through implementation and extensive experimentation. The results show that ASAP significantly outperforms baseline algorithms by returning final top-k result to users in much better times
Quantum one-time programs

A one-time program is a hypothetical device by which a user may evaluate a circuit on exactly one input of his choice, before the device self-destructs. One-time programs cannot be achieved by software alone, as any software can be copied and re-run. However, it is known that every circuit can be compiled into a one-time program using a very basic hypothetical hardware device called a one-time memory. At first glance it may seem that quantum information, which cannot be copied, might also allow for one-time programs. But it is not hard to see that this intuition is false: one-time programs for classical or quantum circuits based solely on quantum information do not exist, even with computational assumptions.\ud
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This observation raises the question, "what assumptions are required to achieve one-time programs for quantum circuits?" Our main result is that any quantum circuit can be compiled into a one-time program assuming only the same basic one-time memory devices used for classical circuits. Moreover, these quantum one-time programs achieve statistical universal composability (UC-security) against any malicious user. Our construction employs methods for computation on authenticated quantum data, and we present a new quantum authentication scheme called the trap scheme for this purpose. As a corollary, we establish UC-security of a recent protocol for delegated quantum computation
How to Run Turing Machines on Encrypted Data

Cryptographic schemes for computing on encrypted data promise to be a fundamental building block of cryptography. The way one models such algorithms has a crucial effect on the efficiency and usefulness of the resulting cryptographic schemes. As of today, almost all known schemes for fully homomorphic encryption, functional encryption, and garbling schemes work by modeling algorithms as circuits rather than as Turing machines.

As a consequence of thismodeling, evaluating an algorithmover encrypted data is as slow as the worst-case running time of that algorithm, a dire fact for many tasks. In addition, in settings where an evaluator needs a description of the algorithm itself in some “encoded” form, the cost of computing and communicating such encoding is as large as the worst-case running time of this algorithm.

In this work, we construct cryptographic schemes for computing Turing machines on encrypted data that avoid the worst-case problem. Specifically, we show:

    An attribute-based encryption scheme for any polynomial-time Turing machine and Random Access Machine (RAM).

    A (single-key and succinct) functional encryption scheme for any polynomialtime Turing machine.

    A reusable garbling scheme for any polynomial-time Turing machine. These three schemes have the property that the size of a key or of a garbling for a Turing machine is very short: it depends only on the description of the Turing machine and not on its running time. Previously, the only existing constructions of such schemes were for depthd circuits, where all the parameters grow with d. Our constructions remove this depth d restriction, have short keys, and moreover, avoid the worst-case running time.

    A variant of fully homomorphic encryption scheme for Turing machines, where one can evaluate a Turing machine M on an encrypted input x in time that is dependent on the running time of M on input x as opposed to the worstcase runtime of M. Previously, such a result was known only for a restricted class of Turing machines and it required an expensive preprocessing phase (with worst-case runtime); our constructions remove both restrictions.

Our results are obtained via a reduction from SNARKs (Bitanski et al) and an “extractable” variant of witness encryption, a scheme introduced by Garg et al.. We prove that the new assumption is secure in the generic group model. We also point out the connection between (the variant of) witness encryption and the obfuscation of point filter functions as defined by Goldwasser and Kalai in 2005
Adaptive multi-agent system for a washing machine production line

This paper describes the implementation of a multi-agent system in a real industrial washing machine production line aiming to integrate process and quality control, allowing the establishment of feedback control loops to support adaptation facing condition changes. For this purpose, the agent-based solution was implemented using the JADE framework, being the shared knowledge structured using a proper ontology, edited and validated in Protégé and posteriorly integrated in the multi-agent system. The solution was intensively tested using historical real production data and it is now being installed in the real production line. The preliminary results confirm the initial expectations in terms of improvement of process performance and product quality
Local pre-processing for node classification in networks : application in protein-protein interaction

Network modelling provides an increasingly popular conceptualisation in a wide range of domains, including the analysis of protein structure. Typical approaches to analysis model parameter values at nodes within the network. The spherical locality around a node provides a microenvironment that can be used to characterise an area of a network rather than a particular point within it. Microenvironments that centre on the nodes in a protein chain can be used to quantify parameters that are related to protein functionality. They also permit particular patterns of such parameters in node-centred microenvironments to be used to locate sites of particular interest. This paper evaluates an approach to index generation that seeks to rapidly construct microenvironment data. The results show that index generation performs best when the radius of microenvironments matches the granularity of the index. Results are presented to show that such microenvironments improve the utility of protein chain parameters in classifying the structural characteristics of nodes using both support vector machines and neural networks
Predicting your next OLAP query based on recent analytical sessions

International audienceIn Business Intelligence systems, users interact with data warehouses by formulating OLAP queries aimed at exploring multidimensional data cubes. Being able to predict the most likely next queries would provide a way to recommend interesting queries to users on the one hand, and could improve the efficiency of OLAP sessions on the other. In particular, query recommendation would proactively guide users in data exploration and improve the quality of their interactive experience. In this paper, we propose a framework to predict the most likely next query and recommend this to the user. Our framework relies on a probabilistic user behavior model built by analyzing previous OLAP sessions and exploiting a query similarity metric. To gain insight in the recommendation precision and on what parameters it depends, we evaluate our approach using different quality assessments
Efficient evaluation of ad-hoc range aggregates

θ-MDA is a flexible and efficient operator for complex ad-hoc multi-dimensional aggregation queries. It separates the specification of aggregation groups for which aggregate values are computed (base table b) and the specification of aggregation tuples from which aggregate values are computed. Aggregation tuples are subsets of the detail table r and are defined by a general θ-condition. The θ-MDA requires one scan of r, during which the aggregates are incrementally updated. In this paper, we propose a two-step evaluation strategy for θ-MDA to optimize the computation of ad-hoc range aggregates by reducing them to point aggregates. The first step scans r and computes point aggregates as a partial intermediate result x̃, which can be done efficiently. The second step combines the point aggregates to the final aggregates. This transformation significantly reduces the number of incremental updates to aggregates and reduces the runtime from (∣∣r∣∣⋅∣∣b∣∣) to (∣∣r∣∣) , provided that ∣∣b∣∣<∣∣r∣∣‾‾‾√ and |x̃| ≈ |b|, which is common for OLAP. An empirical evaluation confirms the analytical results and shows the effectiveness of our optimization: range queries are evaluated with almost the same efficiency as point queries
Axial Quasi-normal modes of Neutron Stars with Exotic Matter

We investigate the axial w quasi-normal modes of neutron stars for 18
realistic equations of state in order to study the influence of hyperons and
quarks on the modes. The study has been developed with a new method based on
Exterior Complex Scaling with variable angle, which allow us to generate pure
outgoing quasi-normal modes. A complete study of the junction conditions has
been done. We have obtained that w-modes can be used to distinguish between
neutron stars with exotic matter and without exotic matter for compact enough
stars.Comment: 4 pages, 1 figure, to appear in Proceedings of Spanish Relativity
  Meeting 2012 (ERE 2012) held in University of Minho, Guimar\~aes, Portugal,
  3-7 September 201
Thick Dirac-Nambu-Goto branes on black hole backgrounds

Thickness corrections to static, axisymmetric Dirac-Nambu-Goto branes
embedded into spherically symmetric black hole spacetimes with arbitrary number
of dimensions are studied. First, by applying a perturbative approximation, it
is found that the thick solutions deviate significantly in their analytic
properties from the thin ones near the axis of the system, and perturbative
approaches around the thin configurations can not provide regular thick
solutions above a certain dimension. For the general case, a non-perturbative,
numerical approach is applied and regular solutions are obtained for arbitrary
brane and bulk dimensions. As a special case, it has been found that
2-dimensional branes are exceptional, as they share their analytic properties
with the thin branes rather than the thick solutions of all other dimensions.Comment: 4 pages, 2 figures, Proceedings of the Spanish Relativity Meeting in
  Portugal ERE201
Phenomenology of Unified Dark Matter models with fast transition

A fast transition between a standard matter-like era and a late
$\Lambda$CDM-like epoch generated by a single Unified Dark Matter component can
explain the observed acceleration of the Universe. UDM models with a fast
transition should be clearly distinguishable from $\Lambda$CDM (and
alternatives) through observations. Here we focus on a particularly simple
model and analyse its viability by studying features of the background model
and properties of the adiabatic UDM perturbations.Comment: 4 pages, 1 figure, Proceedings of the Spanish Relativity Meeting
  ERE2012, University of Minho, Guimar\~aes, Portugal, September 3-7, 201
Parametrized Complexity of Weak Odd Domination Problems

Given a graph $G=(V,E)$, a subset $B\subseteq V$ of vertices is a weak odd
dominated (WOD) set if there exists $D \subseteq V {\setminus} B$ such that
every vertex in $B$ has an odd number of neighbours in $D$. $\kappa(G)$ denotes
the size of the largest WOD set, and $\kappa'(G)$ the size of the smallest
non-WOD set. The maximum of $\kappa(G)$ and $|V|-\kappa'(G)$, denoted
$\kappa_Q(G)$, plays a crucial role in quantum cryptography. In particular
deciding, given a graph $G$ and $k>0$, whether $\kappa_Q(G)\le k$ is of
practical interest in the design of graph-based quantum secret sharing schemes.
The decision problems associated with the quantities $\kappa$, $\kappa'$ and
$\kappa_Q$ are known to be NP-Complete. In this paper, we consider the
approximation of these quantities and the parameterized complexity of the
corresponding problems. We mainly prove the fixed-parameter intractability
(W$[1]$-hardness) of these problems. Regarding the approximation, we show that
$\kappa_Q$, $\kappa$ and $\kappa'$ admit a constant factor approximation
algorithm, and that $\kappa$ and $\kappa'$ have no polynomial approximation
scheme unless P=NP.Comment: 16 pages, 5 figure
Locally constrained homomorphisms on graphs of bounded treewidth and bounded degree.

A homomorphism from a graph G to a graph H is locally bijective, surjective, or injective if its restriction to the neighborhood of every vertex of G is bijective, surjective, or injective, respectively. We prove that the problems of testing whether a given graph G allows a homomorphism to a given graph H that is locally bijective, surjective, or injective, respectively, are NP-complete, even when G has pathwidth at most 5, 4 or 2, respectively, or when both G and H have maximum degree 3. We complement these hardness results by showing that the three problems are polynomial-time solvable if G has bounded treewidth and in addition G or H has bounded maximum degree
Groups with a recursively enumerable irreducible word problem

The notion of the word problem is of fundamental importance in group theory. The irreducible word problem is a closely related concept and has been studied in a number of situations; however there appears to be little known in the case where a finitely generated group has a recursively enumerable irreducible word problem. In this paper we show that having a recursively enumerable irreducible word problem with respect to every finite generating set is equivalent to having a recursive word problem. We prove some further results about groups having a recursively enumerable irreducible word problem, amongst other things showing that there are cases where having such an irreducible word problem does depend on the choice of finite generating set
Data value storage for compressed semi-structured data

Growing user expectations of anywhere, anytime access to information require new types of data representations to be considered. While semi-structured data is a common exchange format, its verbose nature makes files of this type too large to be transferred quickly, especially where only a small part of that data is required by the user. There is consequently a need to develop new models of data storage to support the sharing of small segments of semi-structured data since existing XML compressors require the transfer of the entire compressed structure as a single unit. This paper examines the potential for bisimilarity-based partitioning (i.e. the grouping of items with similar structural patterns) to be combined with dictionary compression methods to produce a data storage model that remains directly accessible for query processing whilst facilitating the sharing of individual data segments. Study of the effects of differing types of bisimilarity upon the storage of data values identified the use of both forwards and backwards bisimilarity as the most promising basis for a dictionary-compressed structure. A query strategy is detailed that takes advantage of the compressed structure to reduce the number of data segments that must be accessed (and therefore transferred) to answer a query. A method to remove redundancy within the data dictionaries is also described and shown to have a positive effect on memory usage
Evaluating the Interest of Revamping Past Search Results

In this paper we present two contributions: a method to construct simulated document collections suitable for information retrieval evaluation as well as an approach of information retrieval using past queries and based on result combination. Exponential and Zipf distribution as well as Bradford’s law are applied to construct simulated document collections suitable for information retrieval evaluation. Experiments comparing a traditional retrieval approach with our approach based on past queries using past queries show encouraging improvements using our approach