TOSCA4QC: Two Modeling Styles for TOSCA to Automate the Deployment and Orchestration of Quantum Applications

Wild, Karoline; Breitenbücher, Uwe; Harzenetter, Lukas; Leymann, Frank; Vietz, Daniel; Zimmermann, Michael

doi:10.1109/edoc49727.2020.00024

Cited by 19 publications

(12 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the building blocks of TOSCA modelling language mainly focus on automatic deployment and orchestration of generic cloud applications [6] and do not deal with controlling the flow of data inside such systems [7]. The challenge arises when data-intensive applications need to be designed and orchestrated.…”

Section: Motivation and Goalmentioning

confidence: 99%

“…Along with commercial and non-profit organisations, TOSCA has been widely adopted in other technologies, such as the Internet of Things (IoT) [23] [24] [25], Network Function Virtualization (NFV) [26] [27,28], quantum computing [6], fog and mobile edge computing [27]. TOSCA is mainly designed and developed to improve the portability and interoperability of the cloud technology [29].…”

Section: Literature Survey On Toscamentioning

confidence: 99%

See 1 more Smart Citation

TOSCAdata: Modelling data pipeline applications in TOSCA

Dehury,

Jakovits,

Srirama

et al. 2021

Preprint

View full text Add to dashboard Cite

The serverless platform allows a customer to effectively use cloud resources and pay for the exact amount of used resources. A number of dedicated open source and commercial cloud data management tools are available to handle the massive amount of data. Such modern cloud data management tools are not enough matured to integrate the generic cloud application with the serverless platform due to the lack of mature and stable standards. One of the most popular and mature standards, TOSCA (Topology and Orchestration Specification for Cloud Applications), mainly focuses on application and service portability and automated management of the generic cloud application components. This paper proposes the extension of the TOSCA standard, TOSCAdata, that focuses on the modeling of data pipeline-based cloud applications. Keeping the requirements of modern data pipeline cloud applications, TOSCAdata provides a number of TOSCA models that are independently deployable, schedulable, scalable, and re-usable, while effectively handling the flow and transformation of data in a pipeline manner. We also demonstrate the applicability of proposed TOSCAdata models by taking a web-based cloud application in the context of tourism promotion as a use case scenario.

show abstract

Section: Motivation and Goalmentioning

confidence: 99%

Section: Literature Survey On Toscamentioning

confidence: 99%

TOSCAdata: Modelling data pipeline applications in TOSCA

Dehury,

Jakovits,

Srirama

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…However, a manual deployment and management are time-consuming and error-prone [12,89]. Thus, it must be automated using so-called provisioning or deployment technologies, such as Kubernetes or Terraform [93,95]. For this, all necessary software artifacts and their dependencies are described by a directed acyclic graph, called the topology model [8].…”

Section: Topology Modelingmentioning

confidence: 99%

“…The semantics of the nodes is defined by reusable types shown in brackets [95], e.g., the quantum program is implemented as a Qiskit app and executed using the IBMQ quantum cloud offering. Finally, the nodes in the topology model can be configured using so-called properties, e.g., the token to access IBMQ at runtime as shown at the corresponding node [93].…”

Section: Topology Modelingmentioning

confidence: 99%

See 1 more Smart Citation

The Quantum software lifecycle

Weder

Barzen

Leymann

et al. 2020

Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software

Self Cite

View full text Add to dashboard Cite

With recent advances in the development of more powerful quantum computers, the research area of quantum software engineering is emerging, having the goal to provide concepts, principles, and guidelines to develop high-quality quantum applications. In classical software engineering, lifecycles are used to document the process of designing, implementing, maintaining, analyzing, and adapting software. Such lifecycles provide a common understanding of how to develop and operate an application, which is especially important due to the interdisciplinary nature of quantum computing. Since today's quantum applications are, in most cases, hybrid, consisting of quantum and classical programs, the lifecycle for quantum applications must involve the development of both kinds of programs. However, the existing lifecycles only target the development of quantum or classical programs in isolation. Additionally, the various programs must be orchestrated, e.g., using workflows. Thus, the development of quantum applications also incorporates the workflow lifecycle. In this chapter, we analyze the software artifacts usually comprising a quantum application and present their corresponding lifecycles. Furthermore, we identify the points of connection between the various lifecycles and integrate them into the overall quantum software development lifecycle. Therefore, the integrated lifecycle serves as a basis for the development and execution of hybrid quantum applications.

show abstract

The NISQ Analyzer: Automating the Selection of Quantum Computers for Quantum Algorithms

Salm

Barzen

Breitenbücher

et al. 2020

Communications in Computer and Information Science

Self Cite

View full text Add to dashboard Cite

Quantum computing can enable a variety of breakthroughs in research and industry in the future. Although some quantum algorithms already exist that show a theoretical speedup compared to the best known classical algorithms, the implementation and execution of these algorithms come with several challenges. The input data determines, e.g., the required number of qubits and gates of a quantum algorithm. An algorithm implementation also depends on the used Software Development Kit which restricts the set of usable quantum computers. Because of the limited capabilities of current quantum computers, choosing an appropriate one to execute a certain implementation for a given input is a difficult challenge that requires immense mathematical knowledge about the implemented quantum algorithm as well as technical knowledge about the used Software Development Kits. Thus, we present a roadmap for the automated analysis and selection of implementations of a certain quantum algorithm and appropriate quantum computers that can execute the selected implementation with the given input data.

show abstract

TOSCA4QC: Two Modeling Styles for TOSCA to Automate the Deployment and Orchestration of Quantum Applications

Cited by 19 publications

References 27 publications

TOSCAdata: Modelling data pipeline applications in TOSCA

TOSCAdata: Modelling data pipeline applications in TOSCA

The Quantum software lifecycle

The NISQ Analyzer: Automating the Selection of Quantum Computers for Quantum Algorithms

Contact Info

Product

Resources

About