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Real-Time Stream Data Processing at Scale

Real-Time Stream Data Processing at Scale

引用

IEEE International Conference on Parallel and distributed computing, Applications and Technologies (PDCAT)

作者： M. Reza HoseinyFarahabady Ali Jannesari Wei Bao Zahir Tari Albert Y. Zomaya Center for Distributed & High Performance Computing School of Computer Science The University of Sydney NSW Australia Department of Computer Science Iowa State University IA USA School of Science RMIT University Melbourne VIC Australia

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

A typical scenario in a stream data-flow processing engine is that users submit continues queries in order to receive the computational result once a new stream of data arrives. The focus of the paper is to design a dynamic CPU cap controller for stream data-flow applications with real-time constraints, in which the result of computations must be available within a short time period, specified by the user, once a recent update in the input data occurs. It is common that the stream data-flow processing engine is deployed over a cluster of dedicated or virtualized server nodes, e.g., Cloud or Edge platform, to achieve a faster data processing. However, the attributes of incoming stream data-flow might fluctuate in an irregular way. To effectively cope with such unpredictable conditions, the underlying resource manager needs to be equipped with a dynamic resource provisioning mechanism to ensure the real-time requirements of different applications. The proposed solution uses control theory principals to achieve a good utilization of computing resources and a reduced average response time. The proposed algorithm dynamically adjusts the required quality of service (QoS) in an environment when multiple stream & data-flow processing applications concurrently run with unknown and volatile workloads. Our study confirms that such a unpredictable demand can negatively degrade the system performance, mainly due to adverse interference in the utilization of shared resources. Unlike prior research studies which assumes a static or zero correlation among the performance variability among consolidated applications, we presume the prevalence of shared-resource interference among collocated applications as a key performance-limiting parameter and confront it in scenarios where several applications have different QoS requirements with unpredictable workload demands. We design a low-overhead controller to achieve two natural optimization objectives of minimizing QoS violation amount an

关键词： Resource management Quality of service Data processing Microsoft Windows Adaptation models Computational modeling Real-time systems

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Dynamic Control of CPU Cap Allocations in Stream Processing and Data-Flow Platforms

Dynamic Control of CPU Cap Allocations in Stream Processing ...

引用

IEEE International Symposium on Network computing and Applications

作者： M. Reza HoseinyFarahabady Ali Jannesari Zahir Tari Javid Taheri Albert Y. Zomaya The University of Sydney Center for Distributed & High Performance Computing School of Computer Science New South Wales Australia Iowa State University IA USA RMIT University School of Science Melbourne VIC Australia Karlstad University Sweden

This paper focuses on Timely dataflow programming model for processing streams of data. We propose a technique to define CPU resource allocation (i.e., CPU capping) with the goal to improve response time latency in such type of applications with different quality of service (QoS) level, as they are concurrently running in a shared multi-core computing system with unknown and volatile demand. The proposed solution predicts the expected performance of the underlying platform using an online approach based on queuing theory and adjusts the corrections required in CPU allocation to achieve the most optimized performance. The experimental results confirms that measured performance of the proposed model is highly accurate while it takes into account the percentiles on the QoS metrics. The theoretical model used for elastic allocation of CPU share in the target platform takes advantage of design principals in model predictive control theory and dynamic programming to solve an optimization problem. While the prediction module in the proposed algorithm tries to predict the temporal changes in the arrival rate of each data flow, the optimization module uses a system model to estimate the interference among collocated applications by continuously monitoring the available CPU utilization in individual nodes along with the number of outstanding messages in every intermediate buffer of all TDF applications. The optimization module eventually performs a cost-benefit analysis to mitigate the total amount of QoS violation incidents by assigning the limited CPU shares among collocated applications. The proposed algorithm is robust (i.e., its worst-case output is guaranteed for arbitrarily volatile incoming demand coming from different data streams), and if the demand volatility is not large, the output is optimal, too. Its implementation is done using the TDF framework in Rust for distributed and shared memory architectures. The experimental results show that the proposed algorithm r

关键词： Quality of service Resource management Computational modeling Instruction sets Data models Programming Process control

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A Cache Enhanced Endorser Design for Mitigating performance Degradation in Hyperledger Fabric

A Cache Enhanced Endorser Design for Mitigating Performance ...

引用

IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social computing (CPSCom) Green computing and Communications (GreenCom)

作者： Feng Lu Lu Gan Zhongli Dong Wei Li Hai Jin Albert Y. Zomaya Services Computing Technology and System Lab Huazhong University of Science and Technology China Center for Distributed and High Performance Computing University of Sydney NSW Australia

As a key technology that realises decentralised and highly trusted database management, Blockchain has recently attracted extensive attention. However, the high latency and low throughput in highly concurrent environments is the main performance bottleneck of Blockchain technology, and thus delays its deployment. Although multiple studies have been dedicated to solving the problem of low throughput in Blockchain, they only paid attention to the scenarios with large transactions volume while neglecting the issue of conflicting transactions. In this paper, we demonstrate that the conflict transactions will not only decrease the computing efficiency of Endorser but also slow down the performance of Hyperledger Fabric. Besides, we propose a Cache enhanced Endorser solution to tackle conflict transactions in Hyperledger Fabric vl.0. The experimental results show that our approach can reduce the workload of a node by up to 80%, shorten the turnaround time of transactions by 55%, and improve the computational performance of Endorser up to 1.9 times.

关键词： Blockchain Fabrics Throughput Peer-to-peer computing Security System performance Proposals

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A resource allocation controller for key-value data stores 16

A resource allocation controller for key-value data stores

引用

16th IEEE International Symposium on Network computing and Applications, NCA 2017

作者： Kim, Young Ki Reza Hoseiny, F.M. Lee, Young Choon Zomaya, Albert Y. University of Sydney Center for Distributed and High Performance Computing School of IT Australia Department of Computing Macquarie University Sydney Australia

ISBN: (纸本)9781538614655

Recent distributed key-value data stores, such as Aerospike are getting the momentum with ever-increasing need for large-scale real-time data processing. While these data stores can provide significantly improved performance, they still struggle to meet Quality of Service (QoS) during workload surges. In this paper, we address the problem of QoS-aware resource allocation for burst workloads in key-value data stores. To this end, we design a resource allocation controller, which enables each application to independently regulate the releases of its requests taking into account QoS. In particular, the proposed controller monitors the actual performance metrics of the target system and dynamically releases requests from a buffer owned by each application accordingly. We have implemented the proposed controller in an Aerospike cluster for our performance evaluation. Experiments have been conducted with various workload intensities (with up to 36,180 write operations per second) in comparison with the default Aerospike policy. Experimental results confirm that the proposed controller decreases the overall average latency up to 41% on high-rate workload while maintaining the QoS of high priority applications. © 2017 IEEE.

关键词： Resource allocation

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Exploiting contention and congestion aware switch allocation in network-on-chips 17

Exploiting contention and congestion aware switch allocation...

引用

50th ACM Turing Conference - China, ACM TUR-C 2017

作者： Li, Cunlu Dongy, Dezun Liao, Xiangke National Laboratory for Parallel and Distributed Processing Collaborative Innovation Center of High Performance Computing College of Computer National University of Defense Technology Changsha Hunan410073 China

ISBN: (纸本)9781450348737

Network-on-chip system plays an important role to improve the performance of chip multiprocessor systems. As the complexity of the network increases, congestion problem has become the major performance bottleneck and seriously influence the performance of NoCs. Prior works have focused on designing effective routing algorithm based on collecting congestion and contention information to load balance the traffic. However, most prior works do not consider balancing the traffic load during switch allocation. Due to the lack of congestion information in switch allocation stage, switch allocator performs allocation only based on packet requests and thus aggravates the congestion in the ports of switch. In this paper, we propose to add the congestion and contention information into the switch allocation process and design an efficient on-chip switching strategy which utilizes the contention and congestion information to load balance the traffic and achieve efficient switch allocation. To further enhance the performance of our design, we carefully design our switch allocation strategy to balance the trade-off between traffic load balance and the matching efficiency in switch allocation. We evaluate our design under synthetic traffic and trace of parsec benchmarks. Our evaluations show this mechanism achieves optimal latency compared to best previous switch allocation strategies. © 2017 ACM.

关键词： Network-on-chip

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A resource allocation controller for key-value data stores

A resource allocation controller for key-value data stores

引用

IEEE International Symposium on Network computing and Applications

作者： Young Ki Kim F. M. Reza Hoseiny Young Choon Lee Albert Y. Zomaya The University of Sydney Center for Distributed and High Performance Computing School of IT Australia The University of Sydney Sydney NSW AU Department of Computing Macquarie University Sydney Australia

关键词： Quality of service Resource management Servers Time factors Delays Australia

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An Efficient Label Routing on high-Radix Interconnection Networks

An Efficient Label Routing on High-Radix Interconnection Net...

引用

International Conference on Parallel and distributed Systems (ICPADS)

作者： Fei Lei Dezun Dong Xiangke Liao College of Computer National University of Defense Technology China National Laboratory for Parallel and Distributed Processing National University of Defense Technology China Collaborative Innovation Center of High Performance Computing National University of Defense Technology China

ISBN: (纸本)9781538632086

Cost-effective adaptive routing has a significant impact on overall performance for high-radix hierarchical topologies, such as Dragonfly, which achieve a lower network diameter than traditional topologies, Torus and Fat tree, but exhibit a lower degree of adaptiveness for shortest-path rout- ing. Existing adaptive routing methods for those hierarchical topologies improve the adaptiveness by increasing path length, i.e. local or global adaptive routing, and thus suffer from complex and costly deadlock avoidance. This work aims to maximize the routing adaptiveness at the minimum cost of deadlock avoidance. We propose a label routing method for high-radix hierarchical networks. This label routing utilizes a co-design methodology and coordinates the two pipelines, input queue and routing computation, in the router microarchitec- ture. Packets in the input buffer are labeled by our routing algorithm depending on network states. We reorganize the input buffer and develop a label routing algorithm, named Green-Red Routing, GRR. GRR relaxes the requirement of using virtual channels to eliminate routing deadlock, and mitigates buffer resources dedicated to deadlock avoidance. GRR manages the buffer resources and balance its utilization elaborately, and achieve fully adaptive routing efficiently. We conduct extensive experiments to evaluate the performance of GRR on Dragonfly and compare it with state-of-the-art works. The results show that GRR achieves 10%-35% higher performance than existing routing algorithms under most traffic patterns.

关键词： Routing System recovery Network topology Topology Resource management Adaptive systems Organizations

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Galaxyfly: A novel family of flexible-radix low-diameter topologies for large-scales interconnection networks 16

Galaxyfly: A novel family of flexible-radix low-diameter top...

引用

30th International Conference on Supercomputing, ICS 2016

作者： Lei, Fei Dong, Dezun Liao, Xiangke Su, Xing Li, Cunlu National Laboratory for Parallel and Distributed Processing Collaborative Innovation Center of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450343619

Interconnection network plays an essential role in the architecture of large-scale high performance computing (HPC) systems. In the paper, we construct a novel family of lowdiameter topologies, Galaxyfly, using techniques of algebraic graphs over finite fields. Galaxyfly is guaranteed to retain a small constant diameter while achieving a flexible tradeoff between network scale and bisection bandwidth. Galaxyfly lowers the demands for high radix of network routers and is able to utilize routers with merely moderate radix to build exascale interconnection networks. We present effective congestion-aware routing algorithms for Galaxyfly by exploring its algebraic property. We conduct extensive simulations and analysis to evaluate the performance, cost and power consumption of Galaxyfly against state-of-the-art topologies. The results show that our design achieves better performance than most existing topologies under various routing algorithms and traffic patterns, and is cost-effective to deploy for exascale HPC systems. © 2016 ACM.

关键词： Topology

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Towards Understanding Optimal Load-Balancing of Heterogeneous Short-Range Molecular Dynamics

Towards Understanding Optimal Load-Balancing of Heterogeneou...

引用

IEEE International Conference on high performance computing Workshops (HiPCW)

作者： Steffen Hirschmann Dirk Pflüger Colin W. Glass Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany High Performance Computing Center Stuttgart University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781509057740

For heterogeneous dynamic short-range molecular dynamics simulations it is critical to employ suitable load-balancing methods to minimize the time to solution. However, designing and parametrizing the optimal load-balancing method is a complex task, depending on detailed properties of the simulation *** main challenge in balancing the load of molecular dynamics simulations is the extreme difference in load density for scenarios with heterogeneous particle density, which can easily reach 4-6 orders of magnitude. Therefore, heterogeneity is deemed to be a relevant property and a suitable metric to reliably quantifying heterogeneity is formulated. This metric, which is based on binning particles and evaluating statistical moments, is then applied to example scenarios and correlated to the performance of five load balancing methodologies. Furthermore, how rapidly the load varies over time will determine how long the benefits of a specific partitioning are expected to last. We deem this to be another relevant property, the dynamics, and introduce corresponding metrics. The results indicate that these metric are useful to differentiate between scenarios and facilitate reasoning over the complex relationship between particle simulation scenarios and optimal load balancing methods. This work is a first step towards understanding this relationship, while introducing key concepts we regard as a crucial for this understanding.

关键词： Load modeling Computational modeling Measurement Dynamics Force Partitioning algorithms Load management

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Certificate-free user-friendly HPC access with UNICORE

Certificate-free user-friendly HPC access with UNICORE

引用

UNICORE Summit 2014

作者： Grunzke, Richard Müller-Pfefferkorn, Ralph Center for Information Services and High Performance Computing Department of Distributed and Data Intensive Computing Technische Universität Dresden Dresden Germany

ISBN: (纸本)9783958060043

UNICORE as a middleware to uniformly access computing resources is currently hampered in its daily use by its requirement of using personal certificates. For users these are inconvenient and complex to handle. The latest major release of UNICORE enables its certificate-free deployment using Unity as translating service for external authentication sources such as LDAP. The paper describes the background, the approach taken, experiences and gives an outlook. © UNICORE Summit 2014 - Proceedings. All rights reserved.

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