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IEEE European Technology and Engineering Management Summit (E-TEMS)

作者： Miroshkin, Oleksandr Kovalov, Sergiy Dmitrieva, Olga Shcherbakov, Oleksandr Tsololo, Serhii Dikova, Yuliia Gogolenko, Sergiy Kushnarenko, Volodymyr Svyatnyy, Volodymyr Ulm Univ Commun & Informat Ctr Ulm Germany Donetsk Natl Tech Univ Comp Engn Dept Pokrovsk Ukraine Donetsk Natl Tech Univ Dept Appl Math & Informat Pokrovsk Ukraine HLRS High Performance Comp Ctr Stuttgart Stuttgart Germany

ISBN: (纸本)9781728109039

A citizen's quality of life is always tightly related to the improvement of general technological progress in many subject areas from mechanical and electrical engineering, information technology, mining and technological fields of industry up to biotechnological processes of cellular and molecular dynamics, medicine, and biomechanics of living organisms. It also depends on an achieved level in theory and mathematical description of the internal dynamic processes of different physical nature, simulation of these processes and further practical implementation of the theory into the real technical objects. An important role here plays computing resources which allow to minimize computational time and to increase the complexity of the simulation models. parallel computing systems open for scientists a new level of simulation, but they also set high requirements on specific knowledge and experience of the users. As a result, granting access to computing resources is not sufficient, specialised training of the personnel is also needed. The same problem appears during the integration of a computing centre into the university educational program new courses, workshops and learning materials are required. In this paper, we share our experience and a vision, how modern computing resources could be integrated into university life, what challenges and issues can be expected here. Also, we present a new scientific project between Ukrainian and German academia partners which has a goal to enhance accessibility, usability and improve the system organization of parallel computing resources. The project represents a multidisciplinary research area of parallel Simulation Technology (ParSimTech) and focuses on the creation of the Ukrainian research and training ParSimTech centre.

关键词： high-performance computing research and training centre parallel simulation technology distributed parallel simulation environment

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A Novel, Highly Integrated Simulator for parallel and distributed systems

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ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION 2020年第1期17卷 2-2页

作者： Tampouratzis, Nikolaos Papaefstathiou, Ioannis Nikitakis, Antonios Brokalakis, Andreas Andrianakis, Stamatis Dollas, Apostolos Marcon, Marco Plebani, Emanuele Synelixis Solut Ltd Farmakidou 10 Chalkida 34100 Greece Telecommun Syst Inst Khania Greece Dipartimento Elettron Milan Italy Adv Syst Technol Milan Italy Tech Univ Crete Telecommun Syst Inst Khania 73100 Greece Politecn Milan Dipartimento Elettron Milan Italy STMicroelectronics Adv Syst Technol Geneve Italy

In an era of complex networked parallel heterogeneous systems, simulating independently only parts, components, or attributes of a system-under-design is a cumbersome, inaccurate, and inefficient approach. Moreover, by considering each part of a system in an isolated manner, and due to the numerous and highly complicated interactions between the different components, the system optimization capabilities are severely limited. The presented fully-distributed simulation framework (called as COSSIM) is the first known open-source, high-performance simulator that can handle holistically system-of-systems including processors, peripherals and networks;such an approach is very appealing to both Cyber Physical systems (CPS) and Highly parallel Heterogeneous systems designers and application developers. Our highly integrated approach is further augmented with accurate power estimation and security sub-tools that can tap on all system components and perform security and robustness analysis of the overall system under design-something that was unfeasible up to now. Additionally, a sophisticated Eclipse-based Graphical User Interface (GUI) has been developed to provide easy simulation setup, execution, and visualization of results. COSSIM has been evaluated when executing the widely used Netperf benchmark suite as well as a number of real-world applications. Final results demonstrate that the presented approach has up to 99% accuracy (when compared with the performance of the real system), while the overall simulation time can be accelerated almost linearly with the number of CPUs utilized by the simulator.

关键词： distributed systems simulator parallel systems simulator CPS simulator integrated simulator

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A Holistic Energy-Efficient real-time Scheduler for Mixed Stream and Batch Processing Workloads

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IEEE TRANSACTIONS ON parallel AND distributed systems 2019年第12期30卷 2624-2635页

作者： Maroulis, Stathis Zacheilas, Nikos Kalogeraki, Vana Athens Univ Econ & Business Informat Athens 10434 Greece

In recent years we have experienced a wide adoption of novel distributed processing frameworks such as Apache Spark for handling batch and stream processing big data applications. An important aspect that has not been examined in these systems yet, is the energy consumption during the applications' execution. Reducing the energy consumption of modern datacenters is a necessity, as datacenters contribute over 2 percent of the total US electric usage. However, efficiently scheduling applications in distributed processing systems can be challenging as there is a trade-off between minimizing the datacenter & x0027;s energy usage and satisfying the application performance requirements. In this work we propose, ExpREsS, a scheduler for orchestrating the execution of Spark applications in a way that enables us to minimize the energy consumption while ensuring that the applications' performance requirements are met. Our approach exploits time-series segmentation for capturing the applications' energy usage and execution times, and then applies a novel DVFS technique to minimize the energy consumption. In order to tackle the limited number of application & x0027;s profiling runs, we exploit regression techniques to predict the applications' execution times and power consumption. Our detailed experimental evaluation using realistic workloads on our local cluster illustrates the working and benefits of our approach.

关键词： Power demand Energy consumption Sparks Cluster computing Central Processing Unit time-frequency analysis distributed processing distributed systems scheduling green computing apache spark cluster management

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A High-Performance parallel Approach to Image Processing in distributed Computing

A High-Performance Parallel Approach to Image Processing in ...

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International Conference on Application of Information and Communication Technologies (AICT)

作者： Mekhriddin Rakhimov Doniyor Mamadjanov Abulkosim Mukhiddinov Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi Tashkent Uzbekistan

ISBN: (数字)9781728173863

ISBN: (纸本)9781728173870

Digital image processing is an actual task in the digital communication systems, IP-telephony and video conferencing, in digital television, and video surveillance. Digital processing of large video images takes a lot of time, especially if it happens in a real-time system. And, processing speed plays an important role in recognition of objects in video images received from IP-cameras in real time. This requires the use of modern technologies, and fast algorithms that increase the acceleration of digital image processing. Acceleration problems have not been fully resolved till present. Today's realities are such that the development of accelerated image processing programs requires a good knowledge of parallel and distributed computing. Both of these areas are united by the fact that both parallel and distributed software consists of several processes that together solve one common problem. This article proposes an accelerated method for the tasks of recognizing objects in video images received from IP-cameras using parallel and distributed computing technologies.

关键词： Streaming media Video surveillance real-time systems Acceleration distributed computing Task analysis parallel algorithms

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parallel Iteration Algorithm of Roll Angle Based On High-Performance ARM Processor

Parallel Iteration Algorithm of Roll Angle Based On High-Per...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Shiyao Wang Dongguang Li Siyu Xiao School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

The method for calculating the attitude of the projectile requires high real-time performance and a large amount of *** parallel calculation method of the missile-borne signal is studied. For the linear iterative equations in the attitude solution algorithm, a parallel calculation based on Newton method is *** method decomposes linear iterative equations in parallel to form a distributed multi-core parallel solution process, which can effectively optimize the algorithm solution *** were conducted through four sets of data with different data lengths and frame rates to verify the execution efficiency of multi-core parallel computing.

关键词： Multicore processing Computational modeling distributed databases parallel processing Iterative algorithms real-time systems Mathematical model

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Towards distributed Multi-model Learning on Apache Spark for Model-based Recommender 35

Towards Distributed Multi-model Learning on Apache Spark for...

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IEEE 35th International Conference on Data Engineering (ICDE)

作者： Alzogbi, Anas Koleva, Polina Lausen, Georg Univ Freiburg Dept Comp Sci Freiburg Germany

ISBN: (纸本)9781728108902

Model-based approaches for Content-based Filtering (CBF) recommendation have the potential of generating representative users models owing to their ability to learn from users actions. However, the need for training an individual model for each user leads to a scalability issue and brings a high computational cost that contributes to the limited adaptation of model-based approaches as efficient CBF recommenders. This is particularly relevant for production systems where the recommender is expected to serve a large number of users. In this work, we address the efficiency issue of model-based CBF recommender systems and present a new approach for distributed multi-model learning based on Apache Spark. We use Ranking SVM as the underlying recommendation algorithm and present a distributed implementation that allows efficient training of multiple models in parallel using a collection of machines. We demonstrate the efficiency of our approach on a real-world dataset from citeulike and show that our approach can reduce the cost of multi-model learning without affecting the prediction accuracy.

关键词： Content-based Filtering Recommender systems parallel computation Apache Spark

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distributed Reachability Queries on Massive Graphs 24th

Distributed Reachability Queries on Massive Graphs

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24th Int Conference on Database systems for Advanced Applications / 6th Int workshop on Big Data Management and Service / 4th Int workshop on Big Data Quality Management / 3rd Int workshop on Graph Data Management and Analysis

作者： Zhang, Tianming Gao, Yunjun Li, Congzheng Ge, Congcong Guo, Wei Zhou, Qiang Zhejiang Univ Coll Comp Sci & Technol Hangzhou Zhejiang Peoples R China Qingdao Univ Coll Data Sci & Software Engn Qingdao Shandong Peoples R China

ISBN: (纸本)9783030185909;9783030185893

Reachability querying is one of the most fundamental graph problems, and it has many applications in graph analytics and processing. Although a substantial number of algorithms are proposed, most of them are centralized and cannot scale to massive graphs that are distributed across multiple data centers. In this paper, we study the problem of distributed reachability queries, and present an efficient distributed reachability index, called parallel Vertex Labeling (PVL), together with two lemmas to accelerate the query. Using real datasets, we demonstrate that our solutions achieve better indexing performance and significantly outperform the state-of-the-art distributed techniques.

关键词： Graph Reachability query distributed index Algorithm

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Optimal Batch Plants Design on parallel systems: A Comparative Study 33

Optimal Batch Plants Design on Parallel Systems: A Comparati...

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33rd IEEE International parallel and distributed Processing Symposium (IPDPS)

作者： Borisenko, Andrey Gorlatch, Sergei Tambov State Tech Univ Tambov Russia Univ Munster Munster Germany

ISBN: (纸本)9781538655559

We report a comparative study on the development of high-performance software for solving the problem of optimal design of multiproduct batch plants on modern parallel systems. We analyze two main algorithmic approaches to optimization - branch-and-bound and metaheuristic-based - and we develop and compare their parallel implementations on a variety of parallel architectures: multi-core CPU, GPU, and clusters. Our experiments on a real-world case study - optimization of chemical-engineering systems - demonstrate the trade-offs between the run time performance and the quality of solutions achieved by different algorithms on various parallel architectures.

关键词： combinatorial optimization multi-product batch plant design branch-and-bound metaheuristics GPU computing

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DPCP-p: a distributed locking protocol for parallel real-time tasks 20

DPCP-p: a distributed locking protocol for parallel real-tim...

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Proceedings of the 57th ACM/EDAC/IEEE Design Automation Conference

作者： Maolin Yang Zewei Chen Xu Jiang Nan Guan Hang Lei University of Electronic Science and Technology of China (UESTC) Chengdu China Hong Kong Polytechnic University (PolyU) Hong Kong China

ISBN: (纸本)9781450367257

real-time scheduling and locking protocols are fundamental facilities to construct time-critical systems. For parallel real-time tasks, predictable locking protocols are required when concurrent sub-jobs mutually exclusive access to shared resources. This paper for the first time studies the distributed synchronization framework of parallel real-time tasks, where both tasks and global resources are partitioned to designated processors, and requests to each global resource are conducted on the processor on which the resource is partitioned. We extend the distributed Priority Ceiling Protocol (DPCP) for parallel tasks under federated scheduling, with which we proved that a request can be blocked by at most one lower-priority request. We develop task and resource partitioning heuristics and propose analysis techniques to safely bound the task response times. Numerical evaluation (with heavy tasks on 8-, 16-, and 32-core processors) indicates that the proposed methods improve the schedulability significantly compared to the state-of-the-art locking protocols under federated scheduling.

关键词： locking protocols

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real-time cortical simulations: energy and interconnect scaling on distributed systems 27

Real-time cortical simulations: energy and interconnect scal...

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27th Euromicro International Conference on parallel, distributed and Network-Based Processing (PDP)

作者： Simula, Francesco Pastorelli, Elena Paolucci, Pier Stanislao Martinelli, Michele Lonardo, Alessandro Biagioni, Andrea Capone, Cristiano Capuani, Fabrizio Cretaro, Paolo De Bonis, Giulia Lo Cicero, Francesca Pontisso, Luca Vicini, Piero Ammendola, Roberto Ist Nazl Fis Nucl Sez Roma Rome Italy Sapienza Univ Rome PhD Program Behav Neurosci Rome Italy Ist Nazl Fis Nucl Sez Tor Vergata Rome Italy Univ Roma Tor Vergata Dept Elect Engn Rome Italy

ISBN: (纸本)9781728116440

We profile the impact of computation and inter-processor communication on the energy consumption and on the scaling of cortical simulations approaching the real-time regime on distributed computing platforms. Also, the speed and energy consumption of processor architectures typical of standard HPC and embedded platforms are compared. We demonstrate the importance of the design of low-latency interconnect for speed and energy consumption. The cost of cortical simulations is quantified using the Joule per synaptic event metric on both architectures. Reaching efficient real-time on large scale cortical simulations is of increasing relevance for both future bio-inspired artificial intelligence applications and for understanding the cognitive functions of the brain, a scientific quest that will require to embed large scale simulations into highly complex virtual or real worlds. This work stands at the crossroads between the WaveScalES experiment in the Human Brain Project (HBP), which includes the objective of large scale thalamo-cortical simulations of brain states and their transitions, and the ExaNeSt and EuroExa projects, that investigate the design of an ARM-based, low-power High Performance Computing (HPC) architecture with a dedicated interconnect scalable to million of cores;simulation of deep sleep Slow Wave Activity (SWA) and Asynchronous aWake (AW) regimes expressed by thalamo-cortical models are among their benchmarks.

关键词： neural network real-time energy-to-solution interconnect scaling distributed computing

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