Optimizing the Transition Waste in Coded Elastic Computing

Distributed computing, in which a resource-intensive task is divided into subtasks and distributed among different machines, plays a key role in solving large-scale problems, e.g., machine learning for large datasets or massive computational problems arising in genomic research. Coded computing is a recently emerging paradigm where redundancy for distributed computing is introduced to alleviate the impact of slow machines, or stragglers, on the completion time. Motivated by recently available services in the cloud computing industry, e.g., EC2 Spot or Azure Batch, where spare/low-priority virtual machines are offered at a fraction of the price of the on-demand instances but can be preempted in a short notice, we investigate coded computing solutions over elastic resources, where the set of available machines may change in the middle of the computation. Our contributions are two-fold: We first propose an efficient method to minimize the transition waste, a newly introduced concept quantifying the total number of tasks that existing machines have to abandon or take on anew when a machine joins or leaves, for the cyclic elastic task allocation scheme recently proposed in the literature (Yang et al. ISIT'19). We then proceed to generalize such a scheme and introduce new task allocation schemes based on finite geometry that achieve zero transition wastes as long as the number of active machines varies within a fixed range. The proposed solutions can be applied on top of every existing coded computing scheme tolerating stragglers.Comment: 16 page

A Process Framework for Managing Quality of Service in Private Cloud

As information systems leaders tap into the global market of cloud computing-based services, they struggle to maintain consistent application performance due to lack of a process framework for managing quality of service (QoS) in the cloud. Guided by the disruptive innovation theory, the purpose of this case study was to identify a process framework for meeting the QoS requirements of private cloud service users. Private cloud implementation was explored by selecting an organization in California through purposeful sampling. Information was gathered by interviewing 23 information technology (IT) professionals, a mix of frontline engineers, managers, and leaders involved in the implementation of private cloud. Another source of data was documents such as standard operating procedures, policies, and guidelines related to private cloud implementation. Interview transcripts and documents were coded and sequentially analyzed. Three prominent themes emerged from the analysis of data: (a) end user expectations, (b) application architecture, and (c) trending analysis. The findings of this study may help IT leaders in effectively managing QoS in cloud infrastructure and deliver reliable application performance that may help in increasing customer population and profitability of organizations. This study may contribute to positive social change as information systems managers and workers can learn and apply the process framework for delivering stable and reliable cloud-hosted computer applications

Estudi bibliomètric any 2014. Campus del Baix Llobregat: EETAC i ESAB

En el present informe s’analitza la producció científica de les dues escoles del Campus del Baix Llobregat, l’Escola d’Enginyeria de Telecomunicació i Aerospacial de Castelldefels (EETAC) i l’Escola Superior d’Agricultura de Barcelona (ESAB) durant el 2014.Postprint (author’s final draft

Accurate Energy Barriers for Catalytic Reaction Pathways: An Automatic Training Protocol for Machine Learning Force Fields

In this study, we introduce a training protocol for developing machine learning force fields (MLFFs), capable of accurately determining energy barriers in catalytic reaction pathways. The protocol is validated on the extensively explored hydrogenation of carbon dioxide to methanol over indium oxide. With the help of active learning, the final force field obtains energy barriers within 0.05 eV of Density Functional Theory. Thanks to the computational speedup, not only do we reduce the cost of routine in-silico catalytic tasks, but also find a 40\% reduction in the previously established rate-limiting step. Furthermore, we illustrate the importance of finite-temperature effects and compute free energy barriers. The transferability of the protocol is demonstrated on the experimentally relevant, yet unexplored, top-layer reduced indium oxide surface. The ability of MLFFs to enhance our understanding of extensively studied catalysts underscores the need for fast and accurate alternatives to direct ab-intio simulations

Elastic circuits

Elasticity in circuits and systems provides tolerance to variations in computation and communication delays. This paper presents a comprehensive overview of elastic circuits for those designers who are mainly familiar with synchronous design. Elasticity can be implemented both synchronously and asynchronously, although it was traditionally more often associated with asynchronous circuits. This paper shows that synchronous and asynchronous elastic circuits can be designed, analyzed, and optimized using similar techniques. Thus, choices between synchronous and asynchronous implementations are localized and deferred until late in the design process.Peer ReviewedPostprint (published version

Index to NASA tech briefs, 1971

The entries are listed by category, subject, author, originating source, source number/Tech Brief number, and Tech Brief number/source number. There are 528 entries