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    Item type:Publication, Access status: with files ,
    A portable compiler-runtime approach for scalability prediction
    Highly scalable parallel applications can efficiently solve expensive computational problems when run on a large number of compute nodes. However, selecting the optimal number of nodes for a compute job of a given size is non-trivial, and allocating too few or too many nodes may not yield the expected performance. Knowing the scaling behavior of an application in advance enables us, for example, to make optimal use of the available hardware resources. We introduce a novel, portable approach to predict the scalability of parallel applications written in modern high-level programming models. We propose a predictive compiler-runtime framework based on Celerity, a task-based distributed runtime system that enables executing SYCL codes on clusters. The framework targets a broad range of computing systems, from CPU to GPU clusters, and proposes a model that combines machine learning, communication modeling and DAG heuristics. Experimental results on two large-scale clusters, JUWELS and Marconi-100, show accurate scalability prediction of unseen single and multi-task applications.
    Publicationtype: Journal Article
      35  15
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    Item type:Publication,
    Cost-efficient auto-scaling of container-based elastic processes
    In business process landscapes, a common challenge is to provide the necessary computational resources to enact the single process steps. One well-known approach to solve this issue in a cost-efficient way is to use the notion of elasticity, i.e., to provide cloud-based computational resources in a rapid fashion and to enact the single process steps on these resources. Existing approaches to provide elastic processes are mostly based on Virtual Machines (VMs). Utilizing container technologies could enable a more fine-grained allocation of process steps to computational resources, leading to a better resource utilization and improved cost efficiency. In this paper, we propose an approach to optimize resource allocation for elastic processes by applying a four-fold auto-scaling approach. The main goal is to minimize the cost of process enactments by using containers. To this end, we formulate and implement a multi-objective optimization problem applying Mixed-Integer Linear Programming and use a transformation step to allocate software services to containers. We thoroughly evaluate the optimization problem and show that it can lead to significant cost savings while maintaining Service Level Agreements, compared to approaches that only use VMs.
    Publicationtype: Journal Article
      44
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    Item type:Publication,
    Runtime verification for business processes utilizing the Bitcoin blockchain
    The usage of process choreographies and decentralized Business Process Management Systems has been named as an alternative to centralized business process orchestration. In choreographies, control over a process instance is shared between independent parties, and no party has full control or knowledge during process runtime. Nevertheless, it is necessary to monitor and verify process instances during runtime for purposes of documentation, accounting, or compensation. To achieve business process runtime verification, this work explores the suitability of the Bitcoin blockchain to create a novel solution for choreographies. The resulting approach is realized in a fully-functional software prototype. This software solution is evaluated in a qualitative comparison. Findings show that our blockchain-based approach enables a seamless execution monitoring and verification of choreographies, while at the same time preserving anonymity and independence of the process participants. Furthermore, the prototype is evaluated in a performance analysis.
    Publicationtype: Journal Article
      99
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    Item type:Publication,
    Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud
    With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.
    Publicationtype: Journal Article
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