Relevant bibliographies by topics / Scalable runtime systems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Scalable runtime systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Scalable runtime systems"

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Lim, Sang Boem, Hanku Lee, Bryan Carpenter, and Geoffrey Fox. "Runtime support for scalable programming in Java." Journal of Supercomputing 43, no. 2 (2007): 165–82. http://dx.doi.org/10.1007/s11227-007-0125-5.

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Dong, Zhijiang, Yujian Fu, and Yue Fu. "Runtime Verification on Robotics Systems." International Journal of Robotics Applications and Technologies 3, no. 1 (2015): 23–40. http://dx.doi.org/10.4018/ijrat.2015010102.

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Runtime verification is a technique for generating monitors from formal specification of expected behaviors for the underlying system. It can be applied to automatically evaluate system execution, either on-line or off-line, analyzing extracted execution traces; or it can be used online during operation, potentially steering the application back to a safety region if a property is violated. As a so-called light-weighted formal method, runtime verification bridges the gap between system design and implementation and shorten the distance of software quality assurance between the software testing
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Gao, Jian, Hongmei Wei, Kang Yu, and Peng Qing. "A Scalable Runtime Fault Localization Framework for High-Performance Computing Systems." International Journal of Parallel Programming 46, no. 4 (2017): 749–61. http://dx.doi.org/10.1007/s10766-017-0526-x.

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Bouanaka, Chafia, Ahmed Amar Debza, Faiza Belala, and Nadia Zeghib. "A Formal Framework for Scalable Component-Based Systems." International Journal of Information System Modeling and Design 8, no. 1 (2017): 1–23. http://dx.doi.org/10.4018/ijismd.2017010101.

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Constructing systems from components and building components for different systems require well-established methodologies and processes. This article proposes a formal framework for designing and specifying component-based systems (CBS). The two-dimensional evolutions of CBS are architectural reconfiguration and behavioral adaptation, when user requirements and/or runtime contexts change. This framework provides an incremental design methodology where component interfaces and their corresponding ports are the basic units of software construction, rather than components. Conceptually, interface
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Búr, Márton, Gábor Szilágyi, András Vörös, and Dániel Varró. "Distributed graph queries over models@run.time for runtime monitoring of cyber-physical systems." International Journal on Software Tools for Technology Transfer 22, no. 1 (2019): 79–102. http://dx.doi.org/10.1007/s10009-019-00531-5.

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Abstract Smart cyber-physical systems (CPSs) have complex interaction with their environment which is rarely known in advance, and they heavily depend on intelligent data processing carried out over a heterogeneous and distributed computation platform with resource-constrained devices to monitor, manage and control autonomous behavior. First, we propose a distributed runtime model to capture the operational state and the context information of a smart CPS using directed, typed and attributed graphs as high-level knowledge representation. The runtime model is distributed among the participating
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Afzal, Wasif, Hugo Bruneliere, Davide Di Ruscio, et al. "The MegaM@Rt2 ECSEL project: MegaModelling at Runtime – Scalable model-based framework for continuous development and runtime validation of complex systems." Microprocessors and Microsystems 61 (September 2018): 86–95. http://dx.doi.org/10.1016/j.micpro.2018.05.010.

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Gijsbers, Bert, and Clemens Grelck. "An Efficient Scalable Runtime System for Macro Data Flow Processing Using S-Net." International Journal of Parallel Programming 42, no. 6 (2013): 988–1011. http://dx.doi.org/10.1007/s10766-013-0271-8.

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Binzenhöfer, Andreas, Gerald Kunzmann, and Robert Henjes. "Design and analysis of a scalable algorithm to monitor chord-based p2p systems at runtime." Concurrency and Computation: Practice and Experience 20, no. 6 (2008): 625–41. http://dx.doi.org/10.1002/cpe.1246.

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Yan, Qiben, Jianzhi Lou, Mehmet C. Vuran, and Suat Irmak. "Scalable Privacy-preserving Geo-distance Evaluation for Precision Agriculture IoT Systems." ACM Transactions on Sensor Networks 17, no. 4 (2021): 1–30. http://dx.doi.org/10.1145/3463575.

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Precision agriculture has become a promising paradigm to transform modern agriculture. The recent revolution in big data and Internet-of-Things (IoT) provides unprecedented benefits including optimizing yield, minimizing environmental impact, and reducing cost. However, the mass collection of farm data in IoT applications raises serious concerns about potential privacy leakage that may harm the farmers’ welfare. In this work, we propose a novel scalable and private geo-distance evaluation system, called SPRIDE, to allow application servers to provide geographic-based services by computing the
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Ortiz, Alberto, Alfonso Rodríguez, Raúl Guerra, et al. "A Runtime-Scalable and Hardware-Accelerated Approach to On-Board Linear Unmixing of Hyperspectral Images." Remote Sensing 10, no. 11 (2018): 1790. http://dx.doi.org/10.3390/rs10111790.

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Space missions are facing disruptive innovation since the appearance of small, lightweight, and low-cost satellites (e.g., CubeSats). The use of commercial devices and their limitations in cost usually entail a decrease in available on-board computing power. To face this change, the on-board processing paradigm is advancing towards the clustering of satellites, and moving to distributed and collaborative schemes in order to maintain acceptable performance levels in complex applications such as hyperspectral image processing. In this scenario, hybrid hardware/software and reconfigurable computi
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Dissertations / Theses on the topic "Scalable runtime systems"

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Chang, Hung-Ching. "Measuring, modeling, and optimizing counterintuitive performance phenomena in power-scalable, parallel systems." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/51682.

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The demands of exascale computing systems and applications have pushed for a rapid, continual design paradigm coupled with increasing design complexities from the interaction between the application, the middleware, and the underlying system hardware, which forms a breeding ground for inefficiency. This work seeks to improve system efficiency by exposing the root causes of unexpected performance slowdowns (e.g., lower performance at higher processor speeds) that occur more frequently in power-scalable systems where raw processor speed varies. More precisely, we perform an exhaustive empirical
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Dinan, James S. "Scalable Task Parallel Programming in the Partitioned Global Address Space." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275418061.

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Book chapters on the topic "Scalable runtime systems"

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Basin, David, Matthieu Gras, Srđan Krstić, and Joshua Schneider. "Scalable Online Monitoring of Distributed Systems." In Runtime Verification. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60508-7_11.

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Das, Raja, Yuan-Shin Hwang, Joel Saltz, and Alan Sussman. "Runtime and Compiler Support for Irregular Computations." In Compiler Optimizations for Scalable Parallel Systems. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45403-9_21.

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Ahlbrecht, Tobias, Jürgen Dix, Michael Köster, Philipp Kraus, and Jörg P. M”uller. "A Scalable Runtime Platform for Multiagent-Based Simulation." In Engineering Multi-Agent Systems. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14484-9_5.

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Angskun, Thara, Graham E. Fagg, George Bosilca, Jelena Pješivac-Grbović, and Jack J. Dongarra. "Self-Healing Network for Scalable Fault Tolerant Runtime Environments." In Distributed and Parallel Systems. Springer US, 2007. http://dx.doi.org/10.1007/978-0-387-69858-8_8.

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Loyall, Joseph P., David E. Bakken, Richard E. Schantz, et al. "QoS Aspect Languages and Their Runtime Integration." In Languages, Compilers, and Run-Time Systems for Scalable Computers. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49530-4_22.

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Wen, Chih-Po, Soumen Chakrabarti, Etienne Deprit, Arvind Krishnamurthy, and Katherine Yelick. "Runtime Support for Portable Distributed Data Structures." In Languages, Compilers and Run-Time Systems for Scalable Computers. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-2315-4_9.

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Agrawal, Gagan, Guy Edjlali, Alan Sussman, Jim Humphries, and Joel Saltz. "Runtime Support for Programming in Adaptive Parallel Environments." In Languages, Compilers and Run-Time Systems for Scalable Computers. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-2315-4_18.

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Zhang, Kai, John Mellor-Crummey, and Robert J. Fowler. "Compilation and Runtime Optimizations for Software Distributed Shared Memory." In Languages, Compilers, and Run-Time Systems for Scalable Computers. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-40889-4_14.

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Leberecht, Markus. "The MuSE Runtime System for SCI Clusters: A Flexible Combination of On-Stack Execution and Work Stealing." In SCI: Scalable Coherent Interface. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/10704208_26.

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Gabriel, Edgar. "Runtime Adaptation Techniques for HPC Applications." In Handbook of Research on Scalable Computing Technologies. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-661-7.ch025.

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This chapter discusses runtime adaption techniques targeting high-performance computing applications. In order to exploit the capabilities of modern high-end computing systems, applications and system software have to be able to adapt their behavior to hardware and application characteristics. Using the Abstract Data and Communication Library (ADCL) as the driving example, the chapter shows the advantage of using adaptive techniques to exploit characteristics of the network and of the application. This allows to reduce the execution time of applications significantly and to avoid having to maintain different architecture dependent versions of the source code.
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Conference papers on the topic "Scalable runtime systems"

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Malony, A., B. Mohr, P. Beckman, et al. "Implementing a parallel C++ runtime system for scalable parallel systems." In the 1993 ACM/IEEE conference. ACM Press, 1993. http://dx.doi.org/10.1145/169627.169802.

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Sakizloglou, Lucas, Sona Ghahremani, Thomas Brand, Matthias Barkowsky, and Holger Giese. "Towards highly scalable runtime models with history." In SEAMS '20: IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. ACM, 2020. http://dx.doi.org/10.1145/3387939.3388614.

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Harvey, Paul, Konstantin Bakanov, Ivor Spence, and Dimitrios S. Nikolopoulos. "A Scalable Runtime for the ECOSCALE Heterogeneous Exascale Hardware Platform." In ROSS '16: International Workshop on Runtime and Operating Systems for Supercomputers. ACM, 2016. http://dx.doi.org/10.1145/2931088.2931090.

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Miletto, Marcelo Cogo, and Lucas Schnorr. "OpenMP and StarPU Abreast: the Impact of Runtime in Task-Based Block QR Factorization Performance." In XX Simpósio em Sistemas Computacionais de Alto Desempenho. Sociedade Brasileira de Computação, 2019. http://dx.doi.org/10.5753/wscad.2019.8654.

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Directed Acyclic Graph (DAG) is a high-level abstraction to describe the activities of parallel applications. A DAG contains tasks (nodes) and dependencies (edges) in the task-based programming paradigm. Application performance depends on the choices of the runtime system. Our work intends to evaluate and compare the performance of three different runtime systems, GCC/libgomp, LLVM/libomp, and StarPU for a task-based dense block QR factorization. The obtained results show that while GCC/libgomp achieves up to 5.4% better performance in the best case, it has scalability problems for finegrain p
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Kamatar, Alok V., Ryan D. Friese, and Roberto Gioiosa. "Locality-Aware Scheduling for Scalable Heterogeneous Environments." In 2020 IEEE/ACM International Workshop on Runtime and Operating Systems for Supercomputers (ROSS). IEEE, 2020. http://dx.doi.org/10.1109/ross51935.2020.00011.

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Xinyu Que. "Efficient and scalable runtime for GAS programming models on petascale systems." In 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/scc.2012.6522602.

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Binzenhofer, A., G. Kunzmann, and R. Henjes. "A scalable algorithm to monitor chord-based p2p systems at runtime." In Proceedings 20th IEEE International Parallel & Distributed Processing Symposium. IEEE, 2006. http://dx.doi.org/10.1109/ipdps.2006.1639710.

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Zhu, Jieming, Pinjia He, Zibin Zheng, and Michael R. Lyu. "Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation." In 2014 IEEE 34th International Conference on Distributed Computing Systems (ICDCS). IEEE, 2014. http://dx.doi.org/10.1109/icdcs.2014.40.

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Liao, Xiongfei, and Thambipillai Srikanthan. "A scalable strategy for runtime resource management on NoC based manycore systems." In 2011 International Symposium on Integrated Circuits (ISIC). IEEE, 2011. http://dx.doi.org/10.1109/isicir.2011.6131955.

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Sakizloglou, Lucas, Sona Ghahremani, Matthias Barkowsky, and Holger Giese. "A scalable querying scheme for memory-efficient runtime models with history." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. ACM, 2020. http://dx.doi.org/10.1145/3365438.3410961.

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