Performance Characterization of In-Memory Data Analytics on a Modern Cloud Server

In last decade, data analytics have rapidly progressed from traditional disk-based processing to modern in-memory processing. However, little effort has been devoted at enhancing performance at micro-architecture level. This paper characterizes the performance of in-memory data analytics using Apache Spark framework. We use a single node NUMA machine and identify the bottlenecks hampering the scalability of workloads. We also quantify the inefficiencies at micro-architecture level for various data analysis workloads. Through empirical evaluation, we show that spark workloads do not scale linearly beyond twelve threads, due to work time inflation and thread level load imbalance. Further, at the micro-architecture level, we observe memory bound latency to be the major cause of work time inflation.Comment: Accepted to The 5th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2015

Achieving Robust Self-Management for Large-Scale Distributed Applications

Autonomic managers are the main architectural building blocks for constructing self-management capabilities of computing systems and applications. One of the major challenges in developing self-managing applications is robustness of management elements which form autonomic managers. We believe that transparent handling of the effects of resource churn (joins/leaves/failures) on management should be an essential feature of a platform for self-managing large-scale dynamic distributed applications, because it facilitates the development of robust autonomic managers and hence improves robustness of self-managing applications. This feature can be achieved by providing a robust management element abstraction that hides churn from the programmer. In this paper, we present a generic approach to achieve robust services that is based on finite state machine replication with dynamic reconfiguration of replica sets. We contribute a decentralized algorithm that maintains the set of nodes hosting service replicas in the presence of churn. We use this approach to implement robust management elements as robust services that can operate despite of churn. Our proposed decentralized algorithm uses peer-to-peer replica placement schemes to automate replicated state machine migration in order to tolerate churn. Our algorithm exploits lookup and failure detection facilities of a structured overlay network for managing the set of active replicas. Using the proposed approach, we can achieve a long running and highly available service, without human intervention, in the presence of resource churn. In order to validate and evaluate our approach, we have implemented a prototype that includes the proposed algorithm

Mini-ribozymes and freezing environment: a new scenario for the early RNA world

International audienceThe RNA World hypothesis states that the present-day life, which is based on DNA genomes and protein enzymes, was preceded by a simpler life form based primarily on RNA. During this era, the genetic information resided in the sequence of RNA molecules and the phenotype derived from the catalytic properties of RNA. Though it is a widely accepted scenario, a number of problems remain unsolved. One of the biggest questions is how complex RNAs could evolve, survive and replicate under typically assumed ''warm and wet'' conditions, taking into account that the RNA phosphodiester backbone is chemically unstable under these conditions. We suggest that prebiotic conditions associated with freezing could have been of key importance in the early RNA World, and discuss the role of primitive catalytic RNA in the evolution of RNA size and complexity

ANALYTICAL MODEL OF TEMPERATURE DISTRIBUTION OVER AN ELECTRONIC CIRCUIT BOARD

The thermal model of an electronic circuit board with installed heat dissipating components is presented as a two-dimension steady-state heat conduction problem with multiple sources distributed over a rectangular region. The corresponding energy equation includes a source term and a temperature-dependent term to account for linear heat transfer in z-direction. Boundary conditions are of first type with unique temperature along the perimeter. The integral-transform technique is applied to obtain closed-form integral solution. Assuming that all dissipated components have a rectangular contact area with the plate, multiple integrals for each dissipated sub-region are easily found. A temperature map over the board is calculated from the closed expression with a triple sum of series with respect to each coordinate and source. The error is evaluated by the estimation of the truncated terms. The solution was applied to obtain the temperature distribution over the electronic Driver Plate of the CEP block of the CIMEX Brazilian experiment for flight qualifying of the Optical Block Detector Assembling

Gossip-based service monitoring platform for wireless edge cloud computing

Edge cloud computing proposes to support shared services, by using the infrastructure at the network's edge. An important problem is the monitoring and management of services across the edge environment. Therefore, dissemination and gathering of data is not straightforward, differing from the classic cloud infrastructure. In this paper, we consider the environment of community networks for edge cloud computing, in which the monitoring of cloud services is required. We propose a monitoring platform to collect near real-time data about the services offered in the community network using a gossip-enabled network. We analyze and apply this gossip-enabled network to perform service discovery and information sharing, enabling data dissemination among the community. We implemented our solution as a prototype and used it for collecting service monitoring data from the real operational community network cloud, as a feasible deployment of our solution. By means of emulation and simulation we analyze in different scenarios, the behavior of the gossip overlay solution, and obtain average results regarding information propagation and consistency needs, i.e. in high latency situations, data convergence occurs within minutes.Peer ReviewedPostprint (author's final draft

On a formula of Coll-Gerstenhaber-Giaquinto

Given a bialgebra B we present a unifying approach to deformations of associative algebras A with a left B-module algebra structure. Special deformations of the comultiplication of B yield universal deformation formulas, i.e. define deformations of the multiplicative structure for all B-module algebras A. This allows to derive known formulas of Moyal-Vey (1949) and Coll-Gerstenhaber-Giaquinto (1989) from a more general point of view

Biomedical journals and databases in Russia and Russian language in the former Soviet Union and beyond

In the 20th century, Russian biomedical science experienced a decline from the blossom of the early years to a drastic state. Through the first decades of the USSR, it was transformed to suit the ideological requirements of a totalitarian state and biased directives of communist leaders. Later, depressing economic conditions and isolation from the international research community further impeded its development. Contemporary Russia has inherited a system of medical education quite different from the west as well as counterproductive regulations for the allocation of research funding. The methodology of medical and epidemiological research in Russia is largely outdated. Epidemiology continues to focus on infectious disease and results of the best studies tend to be published in international periodicals. MEDLINE continues to be the best database to search for Russian biomedical publications, despite only a small proportion being indexed. The database of the Moscow Central Medical Library is the largest national database of medical periodicals, but does not provide abstracts and full subject heading codes, and it does not cover even the entire collection of the Library. New databases and catalogs (e.g. Panteleimon) that have appeared recently are incomplete and do not enable effective searching

AIC-AB NET: A Neural Network for Image Captioning with Spatial Attention and Text Attributes

Image captioning is a significant field across computer vision and natural language processing. We propose and present AIC-AB NET, a novel Attribute-Information-Combined Attention-Based Network that combines spatial attention architecture and text attributes in an encoder-decoder. For caption generation, adaptive spatial attention determines which image region best represents the image and whether to attend to the visual features or the visual sentinel. Text attribute information is synchronously fed into the decoder to help image recognition and reduce uncertainty. We have tested and evaluated our AICAB NET on the MS COCO dataset and a new proposed Fashion dataset. The Fashion dataset is employed as a benchmark of single-object images. The results show the superior performance of the proposed model compared to the state-of-the-art baseline and ablated models on both the images from MSCOCO and our single-object images. Our AIC-AB NET outperforms the baseline adaptive attention network by 0.017 (CIDEr score) on the MS COCO dataset and 0.095 (CIDEr score) on the Fashion dataset