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EQC: Ensembled Quantum computing for Variational Quantum Algorithms 22

EQC: Ensembled Quantum Computing for Variational Quantum Alg...

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49th IEEE/ACM Annual international Symposium on Computer Architecture (ISCA)

作者： Stein, Samuel Wiebe, Nathan Ding, Yufei Bo, Peng Kowalski, Karol Baker, Nathan Ang, James Li, Ang Pacific Northwest Natl Lab Richland WA 99354 USA Univ Calif Santa Barbara Santa Barbara CA USA Univ Toronto Toronto ON Canada

ISBN: (纸本)9781450386104

Variational quantum algorithm (VQA), which is comprised of a classical optimizer and a parameterized quantum circuit, emerges as one of the most promising approaches for harvesting the power of quantum computers in the noisy intermediate scale quantum (NISQ) era. However, the deployment of VQAs on contemporary NISQ devices often faces considerable system and time-dependant noise and prohibitively slow training speeds. On the other hand, the expensive supporting resources and infrastructure make quantum computers extremely keen on high utilization. In this paper, we propose a virtualized way of building up a quantum backend for variational quantum algorithms: rather than relying on a single physical device which tends to introduce ever-changing device-specific noise with less reliable performance as time-since-calibration grows, we propose to constitute a quantum ensemble, which dynamically distributes quantum tasks asynchronously across a set of physical devices, and adjusts the ensemble configuration with respect to machine status. In addition to reduced machine-dependant noise, the ensemble can provide significant speedups for VQA training. With this idea, we build a novel VQA training framework called EQC - a distributed gradient-based processor-performance-aware optimization system - that comprises: (i) a system architecture for asynchronous parallel VQA cooperative training;(ii) an analytical model for assessing the quality of a circuit output concerning its architecture, transpilation, and runtime conditions;(iii) a weighting mechanism to adjust the quantum ensemble's computational contribution according to the systems' current performance. Evaluations comprising 500K times' circuit evaluations across 10 IBMQ NISQ devices using a VQE and a QAOA applications demonstrate that EQC can attain error rates very close to the most performant device of the ensemble, while boosting the training speed by 10.5x on average (up to 86x and at least 5.2x). EQC is available at

关键词： Quantum computing Variational Quantum Algorithms distributed computing

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A Novel Framework for Pharmaceutical Supply Chain Management using distributed Ledger and Smart Contracts

A Novel Framework for Pharmaceutical Supply Chain Management...

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international conference on computing and Networking Technology (ICCNT)

作者： Sandip Jangir Ajit Muzumdar Alok Jaiswal Chirag N. Modi Sheetal Chandel C. Vyjayanthi NIT Goa India

Supply chain in industry is a flow of information and goods traversal through multiple suppliers such as raw material suppliers, manufacturers, distributors, retailers and end users. Supply chain management (SCM) helps in smooth monitoring and accounting of information and goods traversal among multiple users. However, the existing supply chain management processes lack in offering transparency of information, user's privacy, timely updates on demand peaks, improper tracing of information, quality management, deal repudiation and trust among users. To address these problems, we propose a novel framework for pharmaceutical supply chain management which uses an ethereum blockchain, a distributed ledger technology. We propose different smart contracts to manage pharmaceutical supply chain processes over an ethereum blockchain. this framework helps in achieving user privacy, transparency of the supplied drug, tracking of drugs, quality management, non-repudiation and demand supply management with the improved trust among the users. At the end, we analyze the proposed framework in terms of fulfilling the pharmaceutical supply chain management requirements.

关键词： Drugs Supply chain management Blockchain Raw materials Smart contracts

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Optimized Stochastic Approaches Based on Sobol Quasirandom Sequences for Fredholm Integral Equations of the Second Kind 10th

Optimized Stochastic Approaches Based on Sobol Quasirandom ...

引用

10th international conference on Numerical Methods and applications, NMA 2022

作者： Todorov, Venelin Dimov, Ivan Georgieva, Rayna Ostromsky, Tzvetan Department of Information Modeling Institute of Mathematics and Informatics Bulgarian Academy of Sciences Acad. Georgi Bonchev Str. Block 8 Sofia1113 Bulgaria Department of Parallel Algorithms Institute of Information and Communication Technologies Bulgarian Academy of Sciences Acad. G. Bonchev Str. Block 25A Sofia1113 Bulgaria

ISBN: (纸本)9783031324116

In this paper three possible approaches to compute linear functionals of the solution of the Fredholm integral equation of the second kind are under consideration: a biased Monte Carlo method based on evaluation of truncated Liouville-Neumann series;transformation of this problem into the problem of computing a finite number of integrals, and an unbiased stochastic approach. In the second case several Monte Carlo algorithms for numerical integration have been applied including optimized stochastic approaches developed in our previous studies. the unbiased stochastic approach has been applied to a multidimensional numerical example. A comprehensive analysis about the reliability and the efficiency of the algorithms has been done. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Monte Carlo methods

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Performance Analysis of a Genetic Algorithm Based System for Wireless Mesh Networks Considering Weibull Distribution, DCF and EDCA

Performance Analysis of a Genetic Algorithm Based System for...

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international conference on Innovative Mobile and Internet Services in Ubiquitous computing (IMIS)

作者： Admir Barolli Tetsuya Oda Ilir Shinko Leonard Barolli Fatos Xhafa Makoto Takizawa Department of Information Technology Aleksander Moisiu University of Durres Durres Albania Department of Information and Communication Engineering Fukuoka Institute of Technology (FIT) Higashi-Ku Fukuoka Japan Faculty of Information Technologies Polytechnic University of Tirana Tirana Albania Department of Languages and Informatics Systems Technical University of Catalonia Barcelona Spain Hosei University Koganei-Shi Tokyo Japan

ISBN: (纸本)9781509009855

Wireless Mesh Networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In this paper, we evaluate the performance of two WMN architectures considering throughput, delay, jitter and fairness index metrics. For simulations, we used ns-3 and Optimized Link State Routing (OLSR). We compare the performance of distributed Coordination Function (DCF) and Enhanced distributed Channel Access (EDCA) for Weibull distribution of mesh clients by sending multiple Constant Bit Rate (CBR) flows in the network. the simulation results show that for I/B WMN, the throughput of both MAC protocols is higher than Hybrid WMN. the delay and jitter of both architectures are almost the same. However, for 10 flows, the delay and jitter of I/B WMN is a lower compared with Hybrid WMN. the fairness index is a almost the same for both WMN architectures.

关键词： Mobile communication Web and internet services Ubiquitous computing

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Hierarchical speech recognition system using MFCC feature extraction and dynamic spiking RSOM

Hierarchical speech recognition system using MFCC feature ex...

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ACIS international conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed computing (SNPD)

作者： Behi Tarek Arous Najet Ellouze Noureddine Laboratory of Signal Universitc Tunis EI Manar Tunisia Laboratory of Signal Image and Information Technologies National Engineering school of tunis Enit Université Tunis El Manar Tunisia

In this paper, we propose new variants of unsupervised and competitive learning algorithms designed to deal with temporal sequences. these algorithms combine features from Spiking Neural Networks (SNNs) and the advantages of the hierarchical self organizing map (HSOM). the first variant named Hierarchical Dynamic recurrent spiking self-organizing map (HD-RSSOM) is characterized by the integration of a temporal controller component to regulate the firing activity of the spiking neurons. the second variant is a hierarchical model which represents a multi-layer extension of HD-RSSOM model. the case study of the proposed HSOM variants is phonemes and words recognition in continuous speech. the applied HSOM variants serve as tools for developing intelligent systems and pursuing artificial intelligence applications.

关键词： Training Speech recognition Neurons Speech Vectors Neural networks Mel frequency cepstral coefficient

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On Post-Generation Data Operations in Secure distributed Storage Systems with Internal Padding

On Post-Generation Data Operations in Secure Distributed Sto...

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international conference on Computer and Information Technology (CIT)

作者： Feng Shen Hai Jiang Zhiqian Xu Department of Computer Science Arkansas State University USA Information Security Group Royal Holloway University of London UK

Secure distributed storage systems can achieve data security and fault resilience by providing encrypted and redundant data segments across multiple computing nodes. However, such systems might face severe performance bottlenecks when frequently tacking data with high consistency demand. this paper proposed a secure distributed storage system based on revised secret sharing scheme with internal padding. Data are saved in multiple coefficients of associated polynomials for high capacity. Shares generated from these polynomials are distributed and can be recollected to retrieve the original data. Post-generation data operations including data insertion, deletion, updating and appending do not require the complete share regeneration. Only affected data portions will be reprocessed and parallel processing is supported if they are interleaved. Performance analyses and experimental results have demonstrated the effectiveness and efficiency of the post-generation data operations.

关键词： Polynomials Cryptography distributed databases Secure storage Performance gain

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Perspective of the Large Scale Data Facility (LSDF) Supporting Nuclear Fusion applications

Perspective of the Large Scale Data Facility (LSDF) Supporti...

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Euromicro conference on parallel, distributed and Network-Based Processing

作者： Rainer Stotzka Volker Hartmann thomas Jejkal Michael Sutter Jos van Wezel Marcus Hardt Ariel García Rainer Kupsch Serguei Bourov Karlsruhe Institute of Technology (KIT) Institute for Data Processing and Electronics (IPE) Karlsruhe Germany Karlsruhe Institute of Technology (KIT) Steinbuch Centre for Computing (SCC) Karlsruhe Germany

To cope with the growing requirements of data intensive scientific experiments, models and simulations the Large Scale Data Facility(LSDF) at KIT aims to support many scientific disciplines. the LSDF is a distributed storage facility at Exabyte scale providing storage, archives, data bases and meta data repositories. Open interfaces and APIs support a variety of access methods to the highly available services for high throughput data applications. Tools for an easy and transparent access allow scientists to use the LSDF without bothering with the internal structures and technologies. In close cooperation with the scientific communities the LSDF provides assistance to efficiently organize data and metadata structures, and develops and deploys community specific software on the directly connected computing infrastructure.

关键词： Communities Software Protocols Standards organizations Organizations Microscopy distributed databases

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Security and Storage Issues in Internet of Floating things Edge-Cloud Data Movement 13th

Security and Storage Issues in Internet of Floating Things E...

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13th international conference on parallel Processing and Applied Mathematics, PPAM 2019

作者： Montella, Raffaele Di Luccio, Diana Kosta, Sokol Castiglione, Aniello Maratea, Antonio Department of Science and Technologies University of Naples Parthenope Naples Italy Department of Electronic Systems Aalborg University Copenhagen Denmark

ISBN: (纸本)9783030432218

Sensors and actuators became first class citizens in technologically pervasive urban environments. However, the full potential of data crowdsourcing is still unexploited in marine coastal areas, due to the challenging operational conditions, extremely unstable network connectivity and security issues in data movement. In this paper, we present the latest specification of our DYNAMO Transfer Protocol (DTP), a platform-independent data mover framework specifically designed for the Internet of Floating things applications, where data collected on board of professional or leisure vessels are stored locally and then moved from the edge to the cloud. We evaluate the performance achieved by the DTP in data movement in a controlled environment. © 2020, Springer Nature Switzerland AG.

关键词： Crowdsourcing

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parallel Set Determination and K-Means Clustering for Data Mining on Telecommunication Networks

Parallel Set Determination and K-Means Clustering for Data M...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Da-Qi Ren Da Zheng Guowei Huang Shujie Zhang Zane Wei The US R&D Center Huawei Technologies Santa Clara CA USA

Data mining (DM) techniques have developed in tandem with the telecommunications market. they are designed to analyze communication behaviors to enable personalized services and reduce customer churn. the major DM process uses data exploration technology to extract data, create predictive models using decision trees, and test and verify the stability and effectiveness of the models. the K-means method segments customers into clusters based on billing, loyalty and payment behaviors to create decision tree-based models. Determining the number of k clusters in a data set with limited prior knowledge of the appropriate value is a common problem that is distinct from solving data clustering issues. Several method categories exist to decide the value of k, but the optimal choice will maximally compress the data inside a single cluster and accurately assign each observation its own cluster. this paper presents a parallel approach for accelerating the determination of k in n observations. We introduce two methods for selecting the initial centroids that save computation iterations in K-means clustering: 1) Carrying centroids forward, 2) Minimum impact. Both approaches are designed to expedite K-means computing and the identification of k.

关键词： Clustering algorithms parallel algorithms Optimization Silicon Merging Data mining Acceleration

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Permutational Genetic Algorithm for the Optimized Assignment of Priorities to Tasks and Messages in distributed Real-Time Systems

Permutational Genetic Algorithm for the Optimized Assignment...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Ekain Azketa Juan P. Uribe Marga Marcos Luis Almeida J. Javier Gutierrez Ikerlan Research Center Software Technologies Mondragon Spain Systems Engineering and Automation University of Basque Country Bilbao Spain Electrical and Computer Engineering University of Porto Porto Portugal Computers and Real-Time University of Cantabria Santander Spain

the assignment of fixed priorities to tasks and messages in distributed real-time systems is known to be an NP-hard problem, and thus there is no optimal method to accomplish it in polynomial time. this fact makes it a suitable problem to be approached with generic search and optimization algorithms. In this paper we propose a genetic algorithm with a permutational solution encoding for the assignment of fixed priorities to tasks and messages in distributed real-time systems using a holistic approach. this paper shows that the genetic algorithm can find more and better schedulable priority assignments than HO PA, which is, as far as we know, one of the best methods for the fixed priority assignment in distributed real-time systems.

关键词： Genetic algorithms Real time systems Program processors Biological cells Encoding Processor scheduling Time factors

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