Near-Optimal Straggler Mitigation for Distributed Gradient Methods

Modern learning algorithms use gradient descent updates to train inferential models that best explain data. Scaling these approaches to massive data sizes requires proper distributed gradient descent schemes where distributed worker nodes compute partial gradients based on their partial and local data sets, and send the results to a master node where all the computations are aggregated into a full gradient and the learning model is updated. However, a major performance bottleneck that arises is that some of the worker nodes may run slow. These nodes a.k.a. stragglers can significantly slow down computation as the slowest node may dictate the overall computational time. We propose a distributed computing scheme, called Batched Coupon's Collector (BCC) to alleviate the effect of stragglers in gradient methods. We prove that our BCC scheme is robust to a near optimal number of random stragglers. We also empirically demonstrate that our proposed BCC scheme reduces the run-time by up to 85.4% over Amazon EC2 clusters when compared with other straggler mitigation strategies. We also generalize the proposed BCC scheme to minimize the completion time when implementing gradient descent-based algorithms over heterogeneous worker nodes

Natural Disasters, Relief Aid, and Household Vulnerability in Pakistan: Evidence from a Pilot Survey in Khyber Pakhtunkhwa

Based on a pilot survey, we analyze the damages caused by floods in Pakistan, 2010, the istribution of aid, and the extent of recovery at he household level. With regard to the nature of damages, we show that flood damages had both between-village and within-village variation, and damages to houses, land (crops), livestock, and other business assets were not highly correlated. In the distribution of aid from outside, we again find substantial between-village and within-village variation - the aid distribution across villages appeared well-targeted toward the severely affected villages, while aid within villages was targeted toward households with larger house damages, but not toward households with larger damages to land, crop, or other assets. The positive aid response to house damages and the negative aid response to the initial wealth level were found but the marginal response of aid to these characteristics was not large. With regard to the recovery from flood damages, we find that aid recipients did not show higher or lower recovery than non-recipients, especially for house damages, which could be due to mixing of a recovery-promoting effect of aid and a selection effect of aid toward households that have more difficulty in recovery. We also show that households who had initially fewer assets and hit by larger flood damages had more difficulty in recovery.natural disaster, relief distribution, resilience, Pakistan

Lagrange Coded Computing: Optimal Design for Resiliency, Security and Privacy

We consider a scenario involving computations over a massive dataset stored distributedly across multiple workers, which is at the core of distributed learning algorithms. We propose Lagrange Coded Computing (LCC), a new framework to simultaneously provide (1) resiliency against stragglers that may prolong computations; (2) security against Byzantine (or malicious) workers that deliberately modify the computation for their benefit; and (3) (information-theoretic) privacy of the dataset amidst possible collusion of workers. LCC, which leverages the well-known Lagrange polynomial to create computation redundancy in a novel coded form across workers, can be applied to any computation scenario in which the function of interest is an arbitrary multivariate polynomial of the input dataset, hence covering many computations of interest in machine learning. LCC significantly generalizes prior works to go beyond linear computations. It also enables secure and private computing in distributed settings, improving the computation and communication efficiency of the state-of-the-art. Furthermore, we prove the optimality of LCC by showing that it achieves the optimal tradeoff between resiliency, security, and privacy, i.e., in terms of tolerating the maximum number of stragglers and adversaries, and providing data privacy against the maximum number of colluding workers. Finally, we show via experiments on Amazon EC2 that LCC speeds up the conventional uncoded implementation of distributed least-squares linear regression by up to $13.43\times$, and also achieves a $2.36\times$-$12.65\times$ speedup over the state-of-the-art straggler mitigation strategies

Copper translocation from preserved wood exposed to wood decay fungi

Na področju zaščite lesa se v zadnjem času pojavljajo na baker odporni sevi gliv, kar v praksi predstavlja velik problem. Tolerantne glive ogrožajo zaščiten les v uporabi z običajno trajnostjo nad 30 let, saj les okužen s tolerantnimi sevi gliv lahko propade že v nekaj letih. Mehanizmi tolerantnosti še niso povsem pojasneni. Velik pomen se pripisuje oksalni kislini, ki jo intenzivno tvorijo tolerantne glive. Z laboratorijskimi poskusismo ugotovili, da je poleg tega mehanizma pomemben tudi aktivni transport bakra v micelij gliv. Pri glivah, ki ne izločajo oksalne kisline, jetranslokacija bakra povzročena z difuzijoCopper tolerance by wood decay fungi is one of the most important problems in the field of wood preservation. These fungi are potential danger for preserved wood in use, wood with expected lifetime of 30 years. Although, the nature of the fungal tolerance is still not completely understood. The resistance of some species of wood decay fungi to copper has been connected to their production of copious amounts of oxalic acid. However, oxalic acid production is not the only factor responsible for this phenomenon. Laboratory experiments showed that one other important mechanism is active copper transport of copper tolerant fungi and diffusion of copper by intolerant one

Illegal waste sites as a potential micro foci of mediterranean leishmaniasis

Apart from being against the law, illegal waste dumping also poses a threat to human health and to the environment. Solid and decomposing waste is an ideal breeding ground for a number of rodents, insects, and other vermin that pose a health risk through the spread of infectious diseases. The main objective of this study was to survey disease vectors and rodents for the presence of Leishmania sp. from waste sites along the Istrian Peninsula in Slovenia and Croatia