Large scale multi-node simulations of ℤ2 gauge theory quantum circuits using Google Cloud Platform

2021 ◽  
Author(s):  
Erik Gustafson ◽  
Burt Holzman ◽  
James Kowalkowski ◽  
Henry Lamm ◽  
Andy C. Y. Li ◽  
...  
Keyword(s):  
Gauge Theory ◽  
Large Scale ◽  
Quantum Circuits ◽  
Cloud Platform

scholarly journals Swarm: A federated cloud framework for large-scale variant analysis

2021 ◽  
Vol 17 (5) ◽  
pp. e1008977
Author(s):  
Amir Bahmani ◽  
Kyle Ferriter ◽  
Vandhana Krishnan ◽  
Arash Alavi ◽  
Amir Alavi ◽  
...  
Keyword(s):  
Time Delays ◽  
Large Scale ◽  
Cloud Platform ◽  
Computational Costs ◽  
Cloud Framework ◽  
Amazon Web Services ◽  
Minimal Data ◽  
Genomic Data Analysis ◽  
Variant Analysis ◽  
Privacy Violation

Genomic data analysis across multiple cloud platforms is an ongoing challenge, especially when large amounts of data are involved. Here, we present Swarm, a framework for federated computation that promotes minimal data motion and facilitates crosstalk between genomic datasets stored on various cloud platforms. We demonstrate its utility via common inquiries of genomic variants across BigQuery in the Google Cloud Platform (GCP), Athena in the Amazon Web Services (AWS), Apache Presto and MySQL. Compared to single-cloud platforms, the Swarm framework significantly reduced computational costs, run-time delays and risks of security breach and privacy violation.

scholarly journals Digitalization of Business Processes of Enterprises of the Ecosystem of Industry 4.0: Virtual-Real Aspect of Economic Growth Reserves

2021 ◽  
Vol 18 ◽  
pp. 569-580
Author(s):  
Kateryna Kraus ◽  
Nataliia Kraus ◽  
Oleksandr Manzhura
Keyword(s):  
Economic Growth ◽  
Virtual Reality ◽  
Data Storage ◽  
Industry 4.0 ◽  
Large Scale ◽  
Business Processes ◽  
Digital Transformation ◽  
Cloud Services ◽  
Scale Production ◽  
Cloud Platform

The purpose of the research is to present the features of digitization of business processes in enterprises as a foundation on which the gradual formation of Industry 4.0 and the search for economic growth in new virtual reality, which has every chance to be a decisive step in implementing digital strategy for Ukraine and development of the innovation ecosystem. Key problems that arise during the digitalization of business processes in enterprises are presented, among which are: the historical orientation of production to mass, “running” sizes and large batches; large-scale production load; the complexity of cooperation and logic between production sites. It is determined that high-quality and effective tools of innovation-digital transformation in the conditions of virtual reality should include: a single system of on-line order management for all enterprises (application registration – technical expertise – planning – performance control – shipment); Smart Factory, Predictive Maintenance, IIoT, CRM, SCM. Features of digital transformation in the part of formation of enterprises of the ecosystem of Industry 4.0 are revealed. The capabilities and benefits of using Azure cloud platform in enterprises, which includes more than 200 products and cloud services, are analyzed. Azure is said to support open source technologies, so businesses have the ability to use tools and technologies they prefer and are more useful. After conducting a thorough analysis of the acceleration of deep digitalization of business processes by enterprises, authors proposed to put into practice Aruba solution for tracking contacts in the fight against COVID-19. Aruba technology helps locate, allowing you to implement flexible solutions based on Aruba Partner Ecosystem using a USB interface. It is proposed to use SYNTEGRA – a data integration service that provides interactive analytics and provides data models and dashboards in order to accelerate the modernization of data storage and management, optimize reporting in the company and obtain real-time analytics. The possibilities of using Azure cloud platform during the digitization of business processes of enterprises of the ecosystem of Industry 4.0 in the conditions of virtual reality are determined.

scholarly journals Advanced exact synthesis of Clifford+T circuits

2020 ◽  
Vol 19 (9) ◽  
Author(s):  
Philipp Niemann ◽  
Robert Wille ◽  
Rolf Drechsler
Keyword(s):  
Large Scale ◽  
Fault Tolerant ◽  
Logic Synthesis ◽  
Research Problem ◽  
Quantum Systems ◽  
Quantum Circuits ◽  
Research Attention ◽  
Small Quantum ◽  
Significant Research ◽  
Important Research Problem

Abstract Quantum systems provide a new way of conducting computations based on the so-called qubits. Due to the potential for significant speed-ups, this field received significant research attention in recent years. The Clifford+T library is a very promising and popular gate library for these kinds of computations. Unlike other libraries considered so far, it consists of only a small number of gates for all of which robust, fault-tolerant realizations are known for many technologies that seem to be promising for large-scale quantum computing. As a consequence, (logic) synthesis of Clifford+T quantum circuits became an important research problem. However, previous work in this area has several drawbacks: Corresponding approaches are either only applicable to very small quantum systems or lead to circuits that are far from being optimal. The latter is mainly caused by the fact that current synthesis realizes the desired circuit by a local, i.e., column-wise, consideration of the underlying unitary transformation matrix to be synthesized. In this paper, we analyze the conceptual drawbacks of this approach and propose to overcome them by taking a global view of the matrices and perform a separation of concerns regarding individual synthesis steps. We precisely describe a corresponding algorithm as well as its efficient implementation on top of decision diagrams. Experimental results confirm the resulting benefits and show improvements of up to several orders of magnitudes in costs compared to previous work.

The Application of Decision Tree Algorithm in Medical Field Based on Cloud Platform

2013 ◽  
Vol 347-350 ◽  
pp. 3397-3402 ◽  
Author(s):  
Zhi Yuan Liu ◽  
Jian Xi Peng ◽  
Yuan Kai Yang
Keyword(s):  
Decision Tree ◽  
Large Scale ◽  
Medical Data ◽  
Medical System ◽  
Seizure Type ◽  
Decision Tree Algorithm ◽  
Cloud Platform ◽  
Tree Algorithm ◽  
Data Process ◽  
Distributed Decision

In the medical system, medical record is summarized, analyzed and predicted a patient seizure type and incidence. With the development of information technology, a large amount of data is to be processed. Traditional analysis algorithm could not be effectively processed to obtain the best predictive results as the data increasing. Decision tree algorithm based on cloud platform is used to record, analyze and predict patients medical data in this paper. A large number of experimental results show that distributed decision tree algorithm proposed in this paper is efficient and could complete prediction work in medical system. The algorithm has good expansibility, its very suitable for large-scale and multitude medical data process.

scholarly journals Dithen: A Computation-as-a-Service Cloud Platform for Large-Scale Multimedia Processing

2019 ◽  
Vol 7 (2) ◽  
pp. 509-523 ◽  
Author(s):  
Joseph Doyle ◽  
Vasileios Giotsas ◽  
Mohammad Ashraful Anam ◽  
Yiannis Andreopoulos
Keyword(s):  
Large Scale ◽  
Cloud Platform ◽  
Multimedia Processing ◽  
Service Cloud

scholarly journals A Secure IoT-Based Cloud Platform Selection Using Entropy Distance Approach and Fuzzy Set Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Alakananda Chakraborty ◽  
Muskan Jindal ◽  
Mohammad R. Khosravi ◽  
Prabhishek Singh ◽  
Achyut Shankar ◽  
...  
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Large Scale ◽  
Service Providers ◽  
Cost Optimization ◽  
Cloud Service ◽  
Security And Privacy ◽  
Cloud Platform ◽  
Efficiency Cost

With the growing emergence of the Internet connectivity in this era of Gen Z, several IoT solutions have come into existence for exchanging large scale of data securely, backed up by their own unique cloud service providers (CSPs). It has, therefore, generated the need for customers to decide the IoT cloud platform to suit their vivid and volatile demands in terms of attributes like security and privacy of data, performance efficiency, cost optimization, and other individualistic properties as per unique user. In spite of the existence of many software solutions for this decision-making problem, they have been proved to be inadequate considering the distinct attributes unique to individual user. This paper proposes a framework to represent the selection of IoT cloud platform as a MCDM problem, thereby providing a solution of optimal efficacy with a particular focus in user-specific priorities to create a unique solution for volatile user demands and agile market trends and needs using optimized distance-based approach (DBA) aided by Fuzzy Set Theory.

scholarly journals An Automated Deployment Engine Based on a PaaS Cloud Platform of the Micro-service Architecture System

2018 ◽  
Vol 227 ◽  
pp. 02020
Author(s):  
Chen Zhong ◽  
Xin Yuan ◽  
Jun Yang
Keyword(s):  
Large Scale ◽  
Cloud Platform ◽  
Service Architecture ◽  
System A ◽  
Management Problems ◽  
Process Deployment

In view of the deployment management problems caused by the service atomization, architecture complexity and large-scale cluster of micro-service architecture system, a PaaS cloud platform automation deployment engine is designed and implemented based on the Docke PaaS platform so as to provide a simple, flexible, efficient, full-stack, full-process deployment solution to the micro service architecture system.

Sign in / Sign up

Export Citation Format

Share Document