A Tight Lower Bound on the Sub-Packetization Level of Optimal-Access MSR and MDS Codes

The first focus of the present paper, is on lower bounds on the sub-packetization level $\alpha$ of an MSR code that is capable of carrying out repair in help-by-transfer fashion (also called optimal-access property). We prove here a lower bound on $\alpha$ which is shown to be tight for the case $d=(n-1)$ by comparing with recent code constructions in the literature. We also extend our results to an $[n,k]$ MDS code over the vector alphabet. Our objective even here, is on lower bounds on the sub-packetization level $\alpha$ of an MDS code that can carry out repair of any node in a subset of $w$ nodes, $1 \leq w \leq (n-1)$ where each node is repaired (linear repair) by help-by-transfer with minimum repair bandwidth. We prove a lower bound on $\alpha$ for the case of $d=(n-1)$. This bound holds for any $w (\leq n-1)$ and is shown to be tight, again by comparing with recent code constructions in the literature. Also provided, are bounds for the case $d<(n-1)$. We study the form of a vector MDS code having the property that we can repair failed nodes belonging to a fixed set of $Q$ nodes with minimum repair bandwidth and in optimal-access fashion, and which achieve our lower bound on sub-packetization level $\alpha$. It turns out interestingly, that such a code must necessarily have a coupled-layer structure, similar to that of the Ye-Barg code.Comment: Revised for ISIT 2018 submissio

Training Big Random Forests with Little Resources

Without access to large compute clusters, building random forests on large datasets is still a challenging problem. This is, in particular, the case if fully-grown trees are desired. We propose a simple yet effective framework that allows to efficiently construct ensembles of huge trees for hundreds of millions or even billions of training instances using a cheap desktop computer with commodity hardware. The basic idea is to consider a multi-level construction scheme, which builds top trees for small random subsets of the available data and which subsequently distributes all training instances to the top trees' leaves for further processing. While being conceptually simple, the overall efficiency crucially depends on the particular implementation of the different phases. The practical merits of our approach are demonstrated using dense datasets with hundreds of millions of training instances.Comment: 9 pages, 9 Figure

Oxygen vacancy enhanced room temperature ferromagnetism in Al-doped MgO nanoparticles

We have investigated the room temperature ferromagnetic order that develops in Al-substituted magnesium oxide, Mg(Al)O, nanoparticles with Al fractions of up to 5 at.%. All samples, including undoped MgO nanoparticles, exhibit room temperature ferromagnetism, with the saturation magnetization reaching a maximum of 0.023 emu/g at 2 at.% of Al. X-ray photoelectron spectroscopy identifies the presence of oxygen vacancies in both doped and undoped MgO nanoparticles, with the vacancy concentration increasing upon vacuum annealing of Mg(Al)O, resulting in two-fold enhancement of the saturation magnetization for 2 at.% Al-doped MgO. Our results suggest that the oxygen vacancies are largely responsible for room temperature ferromagnetism in MgO.Comment: 4 figure

Radiative stability of neutrino-mass textures

Neutrino-mass textures proposed at high-scales are known to be unstable against radiative corrections especially for nearly degenerate eigen values. Within the renormalization group constraints we find a mechanism in a class of gauge theories which guarantees reproduction of any high-scale texture at low energies with radiative stability. We also show how the mechanism explains solar and atmospheric neutrino anomalies through the bimaximal texture at high scale.Comment: 4 pages REVTEX, 1 Postscript fi

A Pluggable Framework for Lightweight Task Offloading in Parallel and Distributed Computing

Multicore processors have quickly become ubiquitous in supercomputing, cluster computing, datacenter computing, and even personal computing. Software advances, however, continue to lag behind. In the past, software designers could simply rely on clock-speed increases to improve the performance of their software. With clock speeds now stagnant, software designers need to tap into the increased horsepower of multiple cores in a processor by creating software artifacts that support parallelism. Rather than forcing designers to write such software artifacts from scratch, we propose a pluggable framework that designers can reuse for lightweight task offloading in a parallel computing environment of multiple cores, whether those cores be colocated on a processor within a compute node, between compute nodes in a tightly-coupled system like a supercomputer, or between compute nodes in a loosely-coupled one like a cloud computer. To demonstrate the efficacy of our framework, we use the framework to implement lightweight task offloading (or software acceleration) for a popular parallel sequence-search application called mpiBLAST. Our experimental results on a 9-node, 36-core AMD Opteron cluster show that using mpiBLAST with our pluggable framework results in a 205% speed-up

Limited growth opportunities amidst opportunities for growth: An empirical study of the inter-firm linkages of small software firms in India

Small firms are important to all economies. This is especially true with the rise of the information and communication technologies (ICTs), as the technical characteristics of information goods lower entry barriers for small firms seeking to take advantage of the growing global demand for ICTs. However, for accessing global markets, or for technological learning, the literature points to the potentially important role of intermediary institutions. This paper examines inter-firm linkages in India, the world's largest exporter of software services, to explore the extent to which large software firms, both foreign multinational corporations (MNCs) and domestic firms, play an intermediary role for the growing number of small firms. Drawing on 172 in-depth, semi-structured interviews, the paper finds that linkages between the large and small firms are few and weak. MNCs prefer working with large domestic firms as they seek the scale to cut costs for labor-intensive services. Large domestic firms too tend not to outsource work to small firms. They prefer independent execution, viewing small firms as potential competition. Any inter-firm links are typically limited to labor contracting and rarely provide access to markets or opportunities for technological learning. Thus, lacking the operational scale, technological or domain diversity, small firms end up dependent on personal networks to access global market opportunities, i.e., despite the growth in opportunities provided by ICTs, the growth opportunities for small software firms in India remain circumscribed