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检索条件"任意字段=24th International European Conference on Parallel and Distributed Computing, Euro-Par 2018"

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24th international european conference on parallel and distributed computing, euro-par 2018

24th International European Conference on Parallel and Distr...

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24th international european conference on parallel and distributed computing, euro-par 2018

ISBN: (纸本)9783319969824

the proceedings contain 57 papers. the special focus in this conference is on parallel and distributed computing. the topics include: Combined Vertical and Horizontal Autoscaling through Model Predictive Control;Early Termination of Failed HPC Jobs through Machine and Deep Learning;peacock: Probe-Based Scheduling of Jobs by Rotating Between Elastic Queues;online Scheduling of Task Graphs on Hybrid Platforms;interference-Aware Scheduling Using Geometric Constraints;resource-Efficient Execution of Conditional parallel Real-Time Tasks;Improving GPU Cache Hierarchy Performance with a Fetch and Replacement Cache;abelian: A Compiler for Graph Analytics on distributed, Heterogeneous Platforms;Using Dynamic Compilation to Achieve Ninja Performance for CNN Training on Many-Core Processors;a Methodology for Performance Analysis of Applications Using Multi-layer I/O;privacy-Preserving Top-k Query Processing in distributed Systems;minimizing Network Traffic for distributed Joins Using Lightweight Locality-Aware Scheduling;VIoLET: A Large-Scale Virtual Environment for Internet of things;adaptive Bandwidth-Efficient Recovery Techniques in Erasure-Coded Cloud Storage;IT Optimization for Datacenters Under Renewable Power Constraint;GPU Provisioning: the 80 - 20 Rule;ECSched: Efficient Container Scheduling on Heterogeneous Clusters;combinatorial Auction Algorithm Selection for Cloud Resource Allocation Using Machine Learning;cloud Federation Formation in Oligopolistic Markets;improving Cloud Simulation Using the Monte-Carlo Method;Runtime Determinacy Race Detection for OpenMP Tasks;Nobody Cares if You Liked Star Wars: KNN Graph Construction on the Cheap;One-Sided Communications for More Efficient parallel State Space Exploration over RDMA Clusters;robust Decentralized Mean Estimation with Limited Communication;snapshot-Based Synchronization: A Fast Replacement for Hand-over-Hand Locking;measuring Multithreaded Message Matching Misery;high-Quality Shared-Memory Graph partitioning.

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Privacy-Preserving Top-k Query Processing in distributed Systems 24th

Privacy-Preserving Top-k Query Processing in Distributed Sys...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Mahboubi, Sakina Akbarinia, Reza Valduriez, Patrick Univ Montpellier INRIA Montpellier France Univ Montpellier LIRMM Montpellier France

ISBN: (纸本)9783319969831;9783319969824

We consider a distributed system that stores user sensitive data across multiple nodes. In this context, we address the problem of privacy-preserving top-k query processing. We propose a novel system, called SD-TOPK, that is able to evaluate top-k queries over encrypted distributed data without needing to decrypt the data in the nodes where they are stored. We implemented and evaluated our system over synthetic and real databases. the results show excellent performance for SD-TOPK compared to baseline approaches.

关键词： Sensitive data

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Task-Based Programming on Emerging parallel Architectures for Finite-Differences Seismic Numerical Kernel 24th

Task-Based Programming on Emerging Parallel Architectures fo...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Moustafa, Salli Kirschenmann, Wilfried Dupros, Fabrice Aochi, Hideo ANEO Boulogne France Bur Rech Geol & Minieres Orleans France

ISBN: (纸本)9783319969831;9783319969824

In recent years, heterogeneous hardware have generalized in almost all supercomputer nodes, requiring a profound shift on the way numerical applications are implemented. this paper, illustrates the design and implementation of a seismic wave propagation simulator, based on the finite-differences numerical scheme, and specifically tailored for such massively parallel hardware infrastructures. the application data-flow is built on top of parSEC, a generic task-based runtime system. the numerical kernels, designed for maximizing data reuse can efficiently leverage large SIMD units available in modern CPU cores. A strong scalability study on a cluster of Intel KNL processors illustrates the application performances.

关键词： High-performance computing C plus plus generic programming SIMD Task-based runtime system parSEC Seismic wave propagation

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One-Sided Communications for More Efficient parallel State Space Exploration over RDMA Clusters 24th

One-Sided Communications for More Efficient Parallel State S...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Coti, Camille Evangelista, Sami Petrucci, Laure Univ Paris 13 Sorbonne Paris Cite UMR 7030 LIPNCNRS 99 Ave JB Clement F-93430 Villetaneuse France

ISBN: (纸本)9783319969831;9783319969824

this paper investigates the use of one-sided communications in the context of state space exploration. this operation is often the core component of model checking tools that explores a system state space to look for behaviours deviating from its specification. It basically consists in the exploration of a (usually huge) directed graph whose nodes and edges represent respectively system states and system changes. We revisit the state of the art distributed algorithm and adapt it to RDMA clusters with an implementation over the OpenSHMEM library and report on preliminary experiments conducted on the Grid'5000 cluster. this asynchronous approach thus reduces the significant communication costs induced by process synchronisation in two-sided communications.

关键词： Directed graphs

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Diagnosing Highly-parallel OpenMP Programs with Aggregated Grain Graphs 24th

Diagnosing Highly-Parallel OpenMP Programs with Aggregated G...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Reissmann, Nico Muddukrishna, Ananya Norwegian Univ Sci & Technol Trondheim Norway

ISBN: (纸本)9783319969831;9783319969824

Grain graphs simplify OpenMP performance analysis by visualizing performance problems from a fork-join perspective that is familiar to programmers However, when programmers decide to expose a high amount of parallelism by creating thousands of task and parallel for-loop chunk instances, the resulting grain graph becomes large and tedious to understand. We present an aggregation method that hierarchically groups related nodes together to reduce grain graphs of any size to one single node. this aggregated graph is then navigated by progressively uncovering groups and following visual clues that guide programmers towards problems while hiding non-problematic regions. Our approach enhances productivity by enabling programmers to understand problems in highly-parallel OpenMP programs with less effort than before.

关键词： Application programming interfaces (API)

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Peacock: Probe-Based Scheduling of Jobs by Rotating Between Elastic Queues 24th

Peacock: Probe-Based Scheduling of Jobs by Rotating Between ...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Khelghatdoust, Mansour Gramoli, Vincent Univ Sydney Data61 CSIRO Sydney NSW Australia

ISBN: (纸本)9783319969831;9783319969824

In this paper, we propose Peacock, a new distributed probe-based scheduler which handles heterogeneous workloads in data analytics frameworks with low latency. Peacock mitigates the Head-of-Line blocking problem, i.e., shorter tasks are enqueued behind the longer tasks, better than the state-of-the-art. To this end, we introduce a novel probe rotation technique. Workers form a ring overlay network and rotate probes using elastic queues. It is augmented by a novel probe reordering algorithm executed in workers. We evaluate the performance of Peacock against two state-of-the-art probe-based solutions through both trace-driven simulation and distributed experiment in Spark under various loads and cluster sizes. Our large-scale performance results indicate that Peacock outperforms the state-of-the-art in all cluster sizes and loads. Our distributed experiments confirm our simulation results.

关键词： Scheduling distributed system Load balancing Big data

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the Drivers Behind Blockchain Adoption: the Rationality of Irrational Choices 24th

The Drivers Behind Blockchain Adoption: The Rationality of I...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Koens, Tommy Poll, Erik Radboud Univ Nijmegen Nijmegen Netherlands

ISBN: (纸本)9783030105495;9783030105488

there has been a huge increase in interest in blockchain technology. However, little is known about the drivers behind the adoption of this technology. In this paper we identify and analyze these drivers, using three real-world and representative scenarios. We confirm in our analysis that blockchain is not an appropriate technology for some scenarios, from a purely technical point of view. the choice for blockchain technology in such scenarios may therefore seem as an irrational choice. However, our analysis reveals that there are non-technical drivers at play that drive the adoption of blockchain, such as philosophical beliefs, network effects, and economic incentives. these non-technical drivers may explain the rationality behind the choice for blockchain adoption.

关键词： Blockchain distributed ledger Technical drivers Non-technical drivers

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Abelian: A Compiler for Graph Analytics on distributed, Heterogeneous Platforms 24th

Abelian: A Compiler for Graph Analytics on Distributed, Hete...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Gill, Gurbinder Dathathri, Roshan Loc Hoang Lenharth, Andrew Pingali, Keshav Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9783319969831;9783319969824

the trend towards processor heterogeneity and distributed-memory has significantly increased the complexity of parallel programming. In addition, the mix of applications that need to run on parallel platforms today is very diverse, and includes graph applications that typically have irregular memory accesses and unpredictable control-flow. To simplify the programming of graph applications on such platforms, we have implemented a compiler called Abelian that translates shared-memory descriptions of graph algorithms written in the Galois programming model into efficient code for distributed-memory platforms with heterogeneous processors. the compiler manages inter-device synchronization and communication while leveraging state-of-the-art compilers for generating device-specific code. the experimental results show that the novel communication optimizations in the Abelian compiler reduce the volume of communication by 23x, enabling the code produced by Abelian to match the performance of handwritten distributed CPU and GPU programs that use the same runtime. the programs produced by Abelian for distributed CPUs are roughly 2.4x faster than those in the Gemini system, a third-party distributed CPU-only system, demonstrating that Abelian can manage heterogeneity and distributed-memory successfully while generating high-performance code.

关键词： Graph analytics Heterogeneous computing distributed computing Compilers High performance computing

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distributed Graph Clustering Using Modularity and Map Equation 24th

Distributed Graph Clustering Using Modularity and Map Equati...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Hamann, Michael Strasser, Ben Wagner, Dorothea Zeitz, Tim Karlsruhe Inst Technol Inst Theoret Informat Karlsruhe Germany

ISBN: (纸本)9783319969831;9783319969824

We study large-scale, distributed graph clustering. Given an undirected graph, our objective is to partition the nodes into disjoint sets called clusters. A cluster should contain many internal edges while being sparsely connected to other clusters. In the context of a social network, a cluster could be a group of friends. Modularity and map equation are established formalizations of this internally-dense-externally-sparse principle. We present two versions of a simple distributed algorithm to optimize both measures. they are based on thrill, a distributed big data processing framework that implements an extended MapReduce model. the algorithms for the two measures, DSLM-Mod and DSLM-Map, differ only slightly. Adapting them for similar quality measures is straight-forward. We conduct an extensive experimental study on real-world graphs and on synthetic benchmark graphs with up to 68 billion edges. Our algorithms are fast while detecting clusterings similar to those detected by other sequential, parallel and distributed clustering algorithms. Compared to the distributed GossipMap algorithm, DSLM-Map needs less memory, is up to an order of magnitude faster and achieves better quality.

关键词： Undirected graphs

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Minimizing Network Traffic for distributed Joins Using Lightweight Locality-Aware Scheduling 24th

Minimizing Network Traffic for Distributed Joins Using Light...

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24th international european conference on parallel and distributed computing (euro-par)

作者： Cheng, Long Murphy, John Liu, Qingzhi Hao, Chunliang theodoropoulos, Georgios Univ Coll Dublin PEL Dublin Ireland Eindhoven Univ Technol Eindhoven Netherlands Chinese Acad Sci Inst Software Beijing Peoples R China Southern Univ Sci & Technol Shenzhen Peoples R China

ISBN: (纸本)9783319969831;9783319969824

Large computing systems such as data centers are becoming the mainstream infrastructures for big data processing. As one of the key data operators in such scenarios, distributed joins is still challenging current techniques since it always incurs a significant cost on network communication. Various advanced approaches have been proposed to improve the performance, however, most of them just focus on data skew handling, and algorithms designed specifically for communication reduction have received less attention. Moreover, although the state-of-the-art technique can minimize network traffic, it provides fine-grained optimal schedules for all individual join keys, which could result in obvious overhead. In this paper, we propose a new approach called LAS (Lightweight Locality-Aware Scheduling), which targets reducing network communication for large distributed joins in an efficient and effective manner. We present the detailed design and implementation of LAS, and conduct an experimental evaluation using large data joins. Our results show that LAS can effectively reduce scheduling overhead and achieve comparable performance on network reduction compared to the state-of-the-art.

关键词： Scheduling

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