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Towards Vertically Scalable Spark applications 24th

Towards Vertically Scalable Spark Applications

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international European conference on parallel and distributed Computing (Euro-Par)

作者： Baresi, Luciano Quattrocchi, Giovanni Politecn Milan Dipartimento Elettron Informaz & Bioingn Piazza Leonardo Da Vinci 32 Milan Italy

ISBN: (纸本)9783030105495;9783030105488

The dynamic provisioning of virtual machines (VMs) supported by many cloud computing infrastructures eases the scalability of software applications. Unfortunately, VMs are relatively slow to boot and public cloud providers do not allow users to vary their resources (vertical scalability) dynamically. To tackle both problems, a few years ago we presented a solution that combines the management of VMs with the use of containers specifically targeted to the efficient runtime management of the resources provisioned to Web applications. This paper borrows from this solution and addresses the problem of provisioning resources to big data, Spark applications at runtime. Spark does not allow for the runtime scalability of the resources associated with its executors, but resources must be provisioned statically. To tackle this problem, the paper describes a container-based version of Spark that supports the dynamic resizing of the memory and CPU cores associated with the different executors. The evaluation demonstrates the feasibility of the approach and identifies the trade-offs involved.

关键词： Containers Big data Spark Resource allocation

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distributed Computing for Smart Meter Data Management for Electrical Utility applications 30

Distributed Computing for Smart Meter Data Management for El...

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30th international conference on Cybernetics and Informatics (K and I)

作者： Zainab, Ameema Refaat, Shady S. Abu-Rub, Haitham Bouhali, Othmane Texas A&M Univ Elect & Comp Engn College Stn TX 77843 USA Texas A&M Univ Elect & Comp Engn Doha Qatar

ISBN: (纸本)9781728143811

With the advent of Internet-of-Things (IoT) devices, including smart meters and sensors in the smart grid, there has been immense research interest in big data management, analytics, and parallel processing of data. However, complex hardware and software parameters configurations and in-depth understanding of the data processing design are essential for efficient utilization of big data analytics platforms. In this work, we analyze the parallelization of load prediction by utilizing spark regression python library to assess the performance with workloads of up to 8 nodes. The results of different configurations have been studied and analyzed against the performance of Apache Spark. It was found that a trade-off between the number of nodes and cores is necessary to perform efficient parallel computing. Multiple sets of combinations of nodes and cores are considered in this paper to evaluate the performance. The work also signifies the importance of high-performance computing capability for smart meters big data management. The obtained results indicate that the computational time is not only dependent on the data size but also on the number of compute nodes and the number of cores assigned to run the job.

关键词： Smart grid load forecast big data parallel computing Apache-Spark high performance computing

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5th international conference on parallel Computing Technologies, PaCT 1999

5th International Conference on Parallel Computing Technolog...

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5th international conference on parallel Computing Technologies, PaCT 1999

ISBN: (纸本)3540663630

The proceedings contain 59 papers. The special focus in this conference is on parallel Computing in Regular Structures. The topics include: Analytical modeling of parallel application in heterogeneous computing environments;skeletons and transformations in an integrated parallel programming environment;sequential unification and aggressive lookahead mechanisms for data memory accesses;a coordination model and facilities for efficient parallel computation;parallelizing of sequential programs on the basis of pipeline and speculative features of the operators;kinetic model of parallel data processing;PSA approach to population models for parallel genetic algorithms;highly accurate numerical methods for incompressible 3D fluid flows on parallel architectures;dynamic task scheduling with precedence constraints and communication delays;two-dimensional scheduling of algorithms with uniform dependencies;consistent lamport clocks for asynchronous groups with process crashes;comparative analysis of learning methods of cellular-neural associative memory;emergence and propagation of round autowave in cellular neural network;routing and embeddings in super cayley graphs;implementing cellular automata based models on parallel architectures;overview, design innovations, and preliminary results;implementing model checking and equivalence checking for time petri nets by the RT-MEC tool;learning concurrent programming;the speedup performance of an associative memory based logic simulator;a high-level programming environment for distributed memory architectures;virtual shared files;an object oriented environment to manage the parallelism of the FIIT applications;performance studies of shared-nothing parallel transaction processing systems;synergetic tool environments and logically instantaneous communication on top of distributed memory parallel machines.

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CORBA lightweight components: A model for distributed component-based heterogeneous computation 7

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7th European conference on parallel Computing, Euro-Par 2001

作者： Sevilla, Diego García, José M. Gómez, Antonio Department of Computer Engineering University of Murcia Spain Department of Information and Communications Engineering University of Murcia Spain

ISBN: (纸本)3540424954

In this article we present CORBA Lightweight Components, CORBA–LC, a new network-centered reflective component model which allows building distributed applications assembling binary independent components spread on the network. It provides a peer network view in which the component dependencies are managed automatically to perform an intelligent application run-time deployment, leading to better utilization of resources. We show the validity of the CORBA–LC approach in dealing with CSCW and Grid Computing applications. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Common object request broker architecture (CORBA)

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Timing optimization of nested loops considering code size for DSP applications

Timing optimization of nested loops considering code size fo...

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Proceedings - 2004 international conference on parallel processing, ICPP 2004

作者： Zhuge, Qingfeng Shao, Zili Sha, Edwin H.-M. Department of Computer Science University of Texas at Dallas Richardson TX 75083 United States

Software pipelining for nested loops remains a challenging problem for embedded system design. The existing software pipelining techniques for single loops can only explore the parallelism of the innermost loop, so the final timing performance is inferior. While multi-dimensional (MD) retiming can explore the outer loop parallelism, it introduces large overheads in loop index generation and code size due to transformation. In this paper, we use MD retiming to model the software pipelining problem of nested loops. We show that the computation time and code size of a software-pipelined loop nest is affected by execution sequence and retiming function. The algorithm of Software Pipelining for NEsted loops technique (SPINE) is proposed to generate fully parallelized loops efficiently with the overheads as small as possible. The experimental results show that our technique outperforms both the standard software pipelining and MD retiming significantly.

关键词： Computer software

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A service architecture for countering distributed denial of service attacks

A service architecture for countering distributed denial of ...

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21st international conference on Advanced Information Networking and applicationsWorkshops/Symposia, AINAW'07

作者： Zaffar, Fareed Kedem, Gershon Department of Computer Science Duke University Box 90129 Durham NC 27708

ISBN: (纸本)0769528473

We present AMP, a novel service architecture for countering distributed denial of service (dDos) attacks. AMP uses dynamically configured network components to perform traffic monitoring, filtering and detection of commonly known attacks. It does not require universal deployment and is complementary to other schemes for countering dDoS attacks, however with the use of collaborative policing techniques, the performance of the scheme can be improved greatly. In addition, it is economically viable, it can be offered as a service to the customers by service providers. We give a detailed design of our system which we implemented on our simulation test-bed. Performance evaluation of our system shows that using our scheme we were able to recover 83% of throughput lost during an attack. © 2007 IEEE.

关键词： Computer crime

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Nasty-MPI: Debugging Synchronization Errors in MPI-3 One-Sided applications 22nd

Nasty-MPI: Debugging Synchronization Errors in MPI-3 One-Sid...

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22nd international conference on parallel and distributed Computing (Euro-Par)

作者： Kowalewski, Roger Fuerlinger, Karl Univ Munich MNM Team Oettingenstr 67 Munich Germany

ISBN: (纸本)9783319436593;9783319436586

The Message Passing Interface (MPI) specifies a one-sided interface for Remote Memory Access (RMA), which allows one process to specify all communication parameters for both the sending and receiving side by providing support for asynchronous reads and updates of distributed shared data. While MPI RMA communication can be highly efficient, proper synchronization of possibly conflicting accesses to shared data is a challenging task. This paper presents a novel debugging tool that supports developers in finding latent synchronization errors. It dynamically intercepts RMA calls and reschedules them into pessimistic executions which are valid in terms of the MPI-3 standard. Given an application with a latent synchronization error, we force a manifestation of this error which can easily be detected with the help of program invariants. An experimental evaluation shows that the tool can uncover synchronization errors which would otherwise likely go unnoticed for a wide range of scenarios.

关键词： Bug detection MPI One-sided communication

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Design and Implementation of 64-bit parallel Prefix Adder

Design and Implementation of 64-bit Parallel Prefix Adder

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2020 IEEE international conference on distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020

作者： Akash Kumar, R. Shetty, Ashish Ashok Saud, Mohammed Serrao, Preemal Sharanya Pinto, Rohan St Joseph Engineering College Department of Electronics and Communication Engineering Mangalore India

ISBN: (纸本)9781728198859

Binary addition is a commonly used application in computational arithmetic. Adders are the basic building blocks of the various computational structures leading to wide applications in Digital Signal processing, arithmetic, and logical units, microprocessors, and microcontrollers. Research on adders with optimal specifications is continuously carried out. The delay of an adder depends on the speed of the carry bit to reach the next bit position for addition. In this paper, we introduce and discuss a fast 64-bit parallel prefix adder design. The proposed novel design uses the advantage of the Ling adder design needed to suppress the area requirement and increase the computation speed compared to the existing algorithms. With a moderate increase in area and power, the adder gives a quality critical path delay of 21.9ns. The structure is coded using Verilog HDL, simulated, and implemented with the Xilinx Vivado tool. © 2020 IEEE.

关键词： Adders

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Workload characterization for operator-based distributed stream processing applications 10

Workload characterization for operator-based distributed str...

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4th ACM international conference on distributed Event-Based Systems, DEBS 2010

作者： Zhang, Xiaolan J. Parekh, Sujay Gedik, Bugra Andrade, Henrique Wu, Kun-Lung University of Illinois Urbana-Champaign IL United States IBM T.J. Watson Research Center Hawthorne NY United States

ISBN: (纸本)9781605589275

Operator-based programming languages provide an effective development model for large scale stream processing applications. A stream processing application consists of many runtime deployable software processing elements (PE) that work in flows to process incoming messages. Operators (OP) are logical building blocks hosted by PEs. One or more OPs can be fused into a PE at compile-time. Performance optimization for our streaming system includes compile-time fusion optimization and runtime PE-to-host deployment. One of the goals of an optimized stream application is to use minimal computing resource to sustain maximal message throughput. Characterizing the resource usage of PEs is critical for performance optimization. During compile-time optimization, OP-level resource usage is used to predict the resource usage of fused PEs. When starting an application, PE-level resource usage is used as an initial estimation by the scheduler. In this paper, we propose an efficient workload characterization approach for data stream processing systems. Our method includes the procedures for obtaining reusable OP-level resource usage information from profiling data and recomposing OP-level profiles to predict PE-level resource usage. We present several techniques to overcome measurement errors from the OP data collection. The impact of hardware speed and multi-threading contention on hyper-threading and multi-core machines are also studied. We show that our method can be applied to several streaming applications and the prediction of the PE CPU resource usage is within 15% of the actual CPU usage. © 2010 ACM.

关键词： Forecasting

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Big Data Testing Framework for Recommendation Systems in e-Science and e-Commerce Domains

Big Data Testing Framework for Recommendation Systems in e-S...

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9th IEEE international conference on Big Data (IEEE BigData)

作者： Uzun-Per, Meryem Can, Ali Burak Gurel, Ahmet Volkan Aktas, Mehmet S. Akdeniz PE TUR AS BiletBank Res & Dev Ctr Istanbul Turkey Istanbul Hlth & Technol Univ Comp Engn Dept Istanbul Turkey Yildiz Tech Univ Comp Engn Dept Istanbul Turkey

ISBN: (纸本)9781665439022

Software testing is an important process to evaluate whether the developed software applications meet the required specifications. There is an emerging need for testing frameworks for big data software projects to ensure the quality of the big data applications and satisfy the user requirements. In this study, we propose a software testing framework that can be utilized in big data projects both in e-science and e-commerce. In particular, we design the proposed framework to test big data-based recommendation applications. To show the usability of the proposed framework, we provide a reference prototype implementation and use the prototype to test a big data recommendation application. We apply the prototype implementation to test both functional and non-functional methods of the recommendation application. The results indicate that the proposed testing framework is usable and efficient for testing the recommendation systems that use big data processing techniques.

关键词： testing framework testing for big data projects recommendation systems big data algorithms distributed systems Spark MLlib

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