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检索条件"任意字段=Proceedings of the Second International Symposium on Databases in Parallel and Distributed Systems"

共 513 条记录，以下是11-20 订阅

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Generalized Flow-Graph Programming Using Template Task-Graphs: Initial Implementation and Assessment

Generalized Flow-Graph Programming Using Template Task-Graph...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Joseph Schuchart Poornima Nookala Mohammad Mahdi Javanmard Thomas Herault Edward F. Valeev George Bosilca Robert J. Harrison Innovative Computing Laboratory The University of Tennessee Knoxville TN USA Institute for Advanced Computational Science Stony Brook University Stony Brook NY USA Meta Platforms Inc New York NY USA Department of Chemistry Virginia Polytechnic Institute and State University Blacksburg VA USA

We present and evaluate TTG, a novel programming model and its C++ implementation that by marrying the ideas of control and data flowgraph programming supports compact specification and efficient distributed execution of dynamic and irregular applications. Programming interfaces that support task-based execution often only support shared memory parallel environments; a few support distributed memory environments, either by discovering the entire DAG of tasks on all processes, or by introducing explicit communications. The first approach limits scalability, while the second increases the complexity of programming. We demonstrate how TTG can address these issues without sacrificing scalability or programmability by providing higher-level abstractions than conventionally provided by task-centric programming systems, without impeding the ability of these runtimes to manage task creation and execution as well as data and resource management efficiently. TTG supports distributed memory execution over 2 different task runtimes, PaRSEC and MADNESS. Performance of four paradigmatic applications (in graph analytics, dense and block-sparse linear algebra, and numerical integrodifferential calculus) with various degrees of irregularity implemented in TTG is illustrated on large distributed-memory platforms and compared to the state-of-the-art implementations.

关键词： Runtime Processor scheduling Scalability distributed databases C++ languages Programming Data models

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HPDC 2020 - proceedings of the 29th international symposium on High-Performance parallel and distributed Computing

HPDC 2020 - Proceedings of the 29th International Symposium ...

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29th international symposium on High-Performance parallel and distributed Computing, HPDC 2020

ISBN: (纸本)9781450370523

The proceedings contain 22 papers. The topics discussed include: spying on the floating point behavior of existing, unmodified scientific applications;high accuracy matrix computations on neural engines: a study of QR factorization and its applications;space-efficient k-d tree-based storage format for sparse tensors;modeling the temporally constrained preemptions of transient cloud VMs;cloud-scale VM-deflation for running interactive applications on transient servers;funcX: a federated function serving fabric for science;towards HPC I/O performance prediction through large-scale log analysis;significantly improving lossy compression for HPC datasets with second-order prediction and parameter optimization;DCDB Wintermute: enabling online and holistic operational data analytics on HPC systems;and FFT-based gradient sparsification for the distributed training of deep neural networks.

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Large scale querying and processing for property graphs PhD symposium 22

Large scale querying and processing for property graphs PhD ...

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22nd international Workshop on Design, Optimization, Languages and Analytical Processing of Big Data, DOLAP 2020

作者： Ragab, Mohamed Data Systems Group University of Tartu Tartu Estonia

Recently, large scale graph data management, querying and processing have experienced a renaissance in several timely application domains (e.g., social networks, bibliographical networks and knowledge graphs). However, these applications still introduce new challenges with large-scale graph processing. Therefore, recently, we have witnessed a remarkable growth in the prevalence of work on graph processing in both academia and industry. Querying and processing large graphs is an interesting and challenging task. Recently, several centralized/distributed large-scale graph processing frameworks have been developed. However, they mainly focus on batch graph analytics. On the other hand, the state-of-the-art graph databases can't sustain for distributed efficient querying for large graphs with complex queries. In particular, online large scale graph querying engines are still limited. In this paper, we present a research plan shipped with the state-of-the-art techniques for large-scale property graph querying and processing. We present our goals and initial results for querying and processing large property graphs based on the emerging and promising Apache Spark framework, a defacto standard platform for big data processing. In principle, the design of this research plan is revolving around two main goals. The first goal focuses on designing an adequate and efficient graph-based storage backend that can be integrated with the Apache Spark framework. The second goal focuses on developing various Graph-aware optimization techniques (e.g., graph indexing, graph materialized views), and extending the default relational Spark Catalyst optimizer with Graph-aware cost-based optimizations. Achieving these contributions can significantly enhance the performance of executing graph queries on top of Apache Spark. © Copyright 2020 for this paper held by its author(s).

关键词： Graph databases

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Biometric systems with Multiuser Access Structures

Biometric Systems with Multiuser Access Structures

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IEEE international symposium on Information Theory (ISIT)

作者： Chou, Remi A. Wichita State Univ Dept Elect Engn & Comp Sci Wichita KS 67260 USA

ISBN: (纸本)9781538692912

We propose a model for biometric systems with a multiuser access structure, where after enrollment only pre-defined authorized sets of participants are allowed to access the system upon presenting their biometrics. Two types of system design are considered for the enrollment. In the first one, the participants must simultaneously present their biometrics to enroll in the system. In the second one, each participant can individually enroll in the system, which is more convenient for systems with a large number of participants. For these two types of enrollment and the presence of a multiuser access structure, the fundamental trade-off between security and privacy leakage is studied.

关键词： Privacy Decoding Encoding distributed databases Biological system modeling Authentication Indexes

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Performance and Stability Analysis of the Task Assignment based on Guessing Size Routing Policy 27

Performance and Stability Analysis of the Task Assignment ba...

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IEEE 27th international symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication systems (MASCOTS)

作者： Bachmat, Eitan Doncel, Josu Sarfati, Hagit Ben Gurion Univ Negev Dept Comp Sci IL-84105 Beer Sheva Israel Univ Basque Country UPV EHU Dept Appl Math Stat & Operat Res Leioa 48940 Spain Ben Gurion Univ Negev Dept Ind Engn IL-84105 Beer Sheva Israel

ISBN: (纸本)9781728149516;9781728149509

In a system formed by parallel servers and one dispatcher, we study the Task Assignment based on Guessing Size (TAGS) policy, an open loop task assignment policy where jobs are non-preemptive, servers are First-Come-First-Served and the size of incoming jobs is not known. This policy works as follows: all the incoming jobs are routed to the first server and jobs that complete service before s(1) units of time leave the system, but jobs that do not complete service before s(1) are killed and they are routed to the second server, where the service starts from scratch. Likewise, jobs that are executed in server i, if they complete service before si units of time, leave the system, whereas jobs that do not complete service before si units of time are killed and routed to the next server. For an arbitrary job size distribution, we provide a necessary and sufficient condition for the stability of a system operating under the TAGS policy. We also analyze the performance of the optimal TAGS policy, i.e., when the cutoffs s(1), s(2), ... are chosen to minimize the waiting time of jobs for an arbitrary job size distribution and we show that it is lower bounded by the performance of the TAGS policy where the maximum queue length is minimized divided by the number of servers minus one. For Bounded Pareto distributed job sizes, we consider the asymptotic regime where the largest job size tends to infinity and we show that, when the system load is less than one, the performance of the optimal TAGS policy is, at most, two times worst than the performance of the optimal SITA policy, which a routing policy where the size of jobs is known. This result shows that the penalty caused by not knowing the size of incoming jobs is upper bounded by a factor of 2. For a higher system load, we show that the order of magnitude of the performance of the optimal TAGS policy in the asymptotic regime depends on the number of spare servers, i.e., the difference between the number of servers in the s

关键词： Queueing theory parallel Servers Heavy-tailed distributions

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Pinot: Realtime OLAP for 530 Million Users 18

Pinot: Realtime OLAP for 530 Million Users

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44th ACM SIGMOD international Conference on Management of Data

作者： Im, Jean-Francois Gopalakrishna, Kishore Subramaniam, Subbu Shrivastava, Mayank Tumbde, Adwait Jiang, Xiaotian Dai, Jennifer Lee, Seunghyun Pawar, Neha Li, Jialiang Aringunram, Ravi LinkedIn Corp Mountain View CA 94043 USA

ISBN: (纸本)9781450317436

Modern users demand analytical features on fresh, real time data. Offering these analytical features to hundreds of millions of users is a relevant problem encountered by many large scale web companies. Relational databases and key-value stores can be scaled to provide point lookups for a large number of users but fall apart at the combination of high ingest rates, high query rates at low latency for analytical queries. Online analytical databases typically rely on bulk data loads and are not typically built to handle nonstop operation in demanding web environments. Offline analytical systems have high throughput but do not offer low query latencies nor can scale to serving tens of thousands of queries per second. We present Pinot, a single system used in production at Linke din that can serve tens of thousands of analytical queries per second, offers near-realtime data ingestion from streaming data sources, and handles the operational requirements of large web properties. We also provide a performance comparison with Druid, a system similar to Pinot.

关键词： parallel and distributed dbmss pinot near real time data ingestion olap

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A Horizontally Scalable and Reliable Architecture for Location-based Publish-Subscribe 36

A Horizontally Scalable and Reliable Architecture for Locati...

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36th IEEE symposium on Reliable distributed systems (SRDS)

作者： Chapuis, Bertil Garbinato, Benoit Mourot, Lucas Univ Lausanne Lausanne Switzerland Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9781538616796

With billions of connected users and objects, location-based services face a massive scalability challenge. We propose a horizontally-scalable and reliable location-based publish/subscribe architecture that can be deployed on a cluster made of commodity hardware. As many modern location-based publish/subscribe systems, our architecture supports moving publishers, as well as moving subscribers. When a publication moves in the range of a subscription, the owner of this subscription is instantly notified via a server-initiated event, usually in the form of a push notification. To achieve this, most existing solutions rely on classic indexing data structures, such as R-trees, and they struggle at scaling beyond the scope of a single computing unit. Our architecture introduces a multi-step routing mechanism that, to achieve horizontal scalability, efficiently combines range partitioning, consistent hashing and a min-wise hashing agreement. In case of node failure, an active replication strategy ensures a reliable delivery of publication throughout the multistep routing mechanism. From an algorithmic perspective, we show that the number of messages required to compute a match is optimal in the execution model we consider and that the number of routing steps is constant. Using experimental results, we show that our method achieves high throughput, low latency and scales horizontally. For example, with a cluster made of 200 nodes, our architecture can process up to 190'000 location updates per second for a fleet of nearly 1'900'000 moving entities, producing more than 130'000 matches per second.

关键词： Internet of Things Publish subscribe systems distributed databases Spatial databases Scalability Fault tolerance

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HPDC 2017 - proceedings of the 26th international symposium on High-Performance parallel and distributed Computing

HPDC 2017 - Proceedings of the 26th International Symposium ...

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26th ACM international symposium on High-Performance parallel and distributed Computing, HPDC 2017

ISBN: (纸本)9781450346993

The proceedings contain 19 papers. The topics discussed include: enabling workflow-aware scheduling on HPC systems;parallel stream processing against workload skewness and variance;NICE: network-integrated cluster-efficient storage;MaDaTS: managing data on tiered storage for scientific workflows;ArrayUDF: user-defined scientific data analysis on arrays;knor: a NUMA-optimized in-memory, distributed and semi-external-memory k-means library;to push or to pull: on reducing communication and synchronization in graph computations;better safe than sorry: grappling with failures of in-memory data analytics frameworks;LetGo: a lightweight continuous framework for HPC applications under failures;towards a more complete understanding of SDC propagation;COS: a parallel performance model for dynamic variations in processor speed, memory speed, and thread concurrency;explaining wide area data transfer performance;predicting output performance of a petascale supercomputer;TCP throughput profiles using measurements over dedicated connections;IOGP: an incremental online graph partitioning algorithm for distributed graph databases;and machine and application aware partitioning for adaptive mesh refinement applications.

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proceedings - 2017 IEEE 16th international symposium on parallel and distributed Computing, ISPDC 2017

Proceedings - 2017 IEEE 16th International Symposium on Para...

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16th IEEE international symposium on parallel and distributed Computing, ISPDC 2017

ISBN: (纸本)9781538608623

The proceedings contain 20 papers. The topics discussed include: contention-aware selective caching to mitigate intra-warp contention on GPUs;an autonomic approach for the selection of robust dynamic loop scheduling techniques;towards the reproducibility of using DLS techniques in scientific applications;exploring the relation between two levels of scheduling using a novel simulation approach;reducing fragmentation on 3D Torus-based HPC systems using packing-based job scheduling and job placement reconfiguration;a bi-objective scheduling approach for energy optimisation of executing and transmitting HPC Applications in decentralised multi-cloud systems;three-tier private cloud application management system with on-site hardware;the performance and scalability of the SHMEM and corresponding MPI-3 routines on a Cray XC30;a new parallelization scheme for the Hermite interpolation based gyroaverage operator;Benchmarking the WRF Model on Bluegene/P, cluster, and cloud platforms and accelerating model setup through parallel genetic algorithms;the OpenDC vision: towards collaborative datacenter simulation and exploration for everybody;on reliability-aware server consolidation in cloud datacenters;accelerating machine learning on sparse datasets with a distributed memory vector architecture;graph-based speculative query execution in relational databases;and understanding the impact of fine-grained data sharing and thread communication on heterogeneous workload development.

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Understanding System Characteristics of Online Erasure Coding on Scalable, distributed and Large-Scale SSD Array systems

Understanding System Characteristics of Online Erasure Codin...

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IEEE international symposium on Workload Characterization (IISWC)

作者： Koh, Sungjoon Zhang, Jie Kwon, Miryeong Yoon, Jungyeon Donofrio, David Kim, Nam Sung Jung, Myoungsoo Yonsei Univ Comp Architecture & Memory Syst Lab Sch Integrated Technol Yonsei Inst Convergence Technol Seoul South Korea Lawrence Berkeley Natl Lab Berkeley CA USA SK Telecom Seoul South Korea Univ Illinois Urbana IL USA

ISBN: (纸本)9781538612330

Large-scale systems with arrays of solid state disks (SSDs) have become increasingly common in many computing segments. To make such systems resilient, we can adopt erasure coding such as Reed-Solomon (RS) code as an alternative to replication because erasure coding can offer a significantly lower storage cost than replication. To understand the impact of using erasure coding on system performance and other system aspects such as CPU utilization and network traffic, we build a storage cluster consisting of approximately one hundred processor cores with more than fifty high-performance SSDs, and evaluate the cluster with a popular open-source distributed parallel file system, Ceph. Then we analyze behaviors of systems adopting erasure coding from the following five viewpoints, compared with those of systems using replication: (1) storage system I/O performance;(2) computing and software overheads;(3) I/O amplification;(4) network traffic among storage nodes;(5) the impact of physical data layout on performance of RS-coded SSD arrays. For all these analyses, we examine two representative RS configurations, which are used by Google and Facebook file systems, and compare them with triple replication that a typical parallel file system employs as a default fault tolerance mechanism. Lastly, we collect 54 block-level traces from the cluster and make them available for other researchers.

关键词： Encoding Arrays Maintenance engineering Layout Performance evaluation distributed databases Reliability

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