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BMA: Bandwidth allocation management for distributed systems under cloud gaming

BMA: Bandwidth allocation management for distributed systems...

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international Conference on Communication Software and Networks, ICCSN

作者： Runze Wang Mochi Xue Kai Chen Zhanqiang Li Tao Dong Youkai Sun Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781479919857

Cloud gaming is becoming a popular IT business among cloud services. In order to host a variety of network services, modern clouds provide great computing power by equipping with multi-core CPUs and parallel-core GPUs. In our previous work, we propose VGASA [1], a virtualized GPU resource adaptive scheduling policy in cloud gaming, solving the poor default mechanisms of GPU resource sharing. However, with the number of game player for cloud gaming rising, the user experience is inevitably limited by the network bandwidth and communication quality, due to the poor default mechanism of network resources management. To address this network limitation, we propose BAM, which combines distributed architecture and virtualized GPU resource adaptive policy in cloud gaming based on our prior work. The key module of BAM maintains a real-time monitoring of the virtual machine (VM) running status to manage the allocation of network resources, guaranteeing the better running of VMs.

关键词： Bandwidth Graphics processing units resource management Games Virtual machining Servers Computer architecture

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Buffer Allocation Based On-Chip Memory Optimization for Many-Core Platforms

Buffer Allocation Based On-Chip Memory Optimization for Many...

引用

IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

作者： Maximilian Odendahl Andrés Goens Rainer Leupers Gerd Ascheid Tomas Henriksson Institute for Communication Technologies and Embedded Systems RWTH Aachen University Germany Huawei Technologies Stockholm Sweden

ISBN: (纸本)9781467376853

The problem of finding an optimal allocation of logical data buffers to memory has emerged as a new research challenge due to the increased complexity of applications and new emerging Dynamic RAM (DRAM) interface technologies. This new opportunity of a large off-chip memory accessible by an ample bandwidth allows to reduce the on-chip Static RAM (SRAM) significantly and save production cost of future manycore platforms. We thus propose changes to an existing work that allows to uniformly reduce the on-chip memory size for a given application. We additionally introduce a novel linear programming model to automatically generate all necessary on chip memory sizes for a given application based on an optimal allocation of data buffers. An extension allows to further reduce the required on-chip memory in multi-application scenarios. We conduct a case study to validate all our models and show the applicability of our approach.

关键词： resource management System-on-chip Random access memory Memory management Optimization Bandwidth Mathematical model

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Towards Balance-Affinity Tradeoff in Concurrent Subgraph Traversals

Towards Balance-Affinity Tradeoff in Concurrent Subgraph Tra...

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international Symposium on parallel and distributed Processing (IPDPS)

作者： Yinglong Xia Lifeng Nai Jui-Hsin Lai IBM Research Yorktown Heights NY USA Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)9781479986507

Graph technologies have been widely utilized for building big data analytics systems. Since those systems are typically wrapped as service providers in industry, it is critical to handle concurrent queries at runtime by incorporating a set of parallel processing units. In many cases, such queries result in local subgraph traversals, which essentially require an efficient scheduling scheme to explore the trade off between the workload balance and the task affinity. In this paper, we present an auction based approach for allocating concurrent subgraph traversals onto the processors. A dynamic weighted bipartite graph is built to model the affinity between subgraph traversals and processors, and the workload of processors. In particular, an edge between a task and a processor in the bipartite graph represents that the data needed by this task is likely cached by this processor. The task vertices and edges are dynamically added or removed, and the heavier edge weight represents stronger belief of the affinity. Besides, the edge weight is also governed by the current workload of the corresponding processor. We perform a parallel auction algorithm to figure out a near-optimal assignment of the subgraph traversal tasks onto the processors, which therefore addresses both the workload balance and the task affinity. The auction algorithm is performed incrementally, so as to capture the changes of the bipartite graph structure. Our experiments show the superior performance of the proposed method for various real-world use cases based on concurrent subgraph traversals.

关键词： Program processors Computer architecture Big data Bipartite graph Tin Processor scheduling resource management

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On the Impact of Execution Models: A Case Study in Computational Chemistry

On the Impact of Execution Models: A Case Study in Computati...

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IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

作者： Daniel Chavarría-Miranda Mahantesh Halappanavar Sriram Krishnamoorthy Joseph Manzano Abhinav Vishnu Adolfy Hoisie Advanced Computing Pacific Northwest National Laboratory Richland WA

ISBN: (纸本)9781467376853

Efficient utilization of high-performance computing (HPC) platforms is an important and complex problem. Execution models, abstract descriptions of the dynamic runtime behavior of the execution stack, have significant impact on the utilization of HPC systems. Using a computational chemistry kernel as a case study and a wide variety of execution models combined with load balancing techniques, we explore the impact of execution models on the utilization of an HPC system. We demonstrate a 50 percent improvement in performance by using work stealing relative to a more traditional static scheduling approach. We also use a novel semi-matching technique for load balancing that has comparable performance to a traditional hyper graph-based partitioning implementation, which is computationally expensive. Using this study, we found that execution model design choices and assumptions can limit critical optimizations such as global, dynamic load balancing and finding the correct balance between available work units and different system and runtime overheads. With the emergence of multi- and many-core architectures and the consequent growth in the complexity of HPC platforms, we believe that these lessons will be beneficial to researchers tuning diverse applications on modern HPC platforms, especially on emerging dynamic platforms with energy-induced performance variability.

关键词： Load modeling Computational modeling Biological system modeling Load management Synthetic aperture sonar Schedules Kernel

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GPU-based parallel R-tree Construction and Querying

GPU-based Parallel R-tree Construction and Querying

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IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

作者： Sushil K. Prasad Michael McDermott Xi He Satish Puri Department of Computer Science Georgia State University Atlanta GA USA

ISBN: (纸本)9781467376853

An R-tree is a data structure for organizing and querying multi-dimensional non-uniform and overlapping data. Efficient parallelization of R-tree is an important problem due to societal applications such as geographic information systems (GIS), spatial database management systems, and VLSI layout which employ R-trees for spatial analysis tasks such as map-overlay. As graphics processing units (GPUs) have emerged as powerful computing platforms, these R-tree related applications demand efficient R-tree construction and search algorithms on GPUs. This problem is hard both due to (i) non-linear tree topology of the data structure itself and (ii) the unconventional single-instruction multiple-thread (SIMT) architecture of modern GPUs requiring careful engineering of a host of issues. Therefore, the current best parallelizations of R-tree on GPU has limited speedup of only about 20-fold. We present a space-efficient data structure design and a non-trivial bottom-up construction algorithm for R-tree on GPUs. This has yielded the first demonstrated 226-fold speedup in parallel construction of an R-tree on a GPU compared to one-core execution on a CPU. We also present innovative R-tree search algorithms that are designed to overcome GPU's architectural and resource limitations. The best of these algorithms gives a speed up of 91-fold to 180-fold on an R-tree with 16384 base objects for query sizes ranging from 2k to 16k.

关键词： Graphics processing units Heuristic algorithms Data structures parallel processing Kernel Instruction sets

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Flexible scheduling and Control of Bandwidth and In-transit Services for End-to-End Application Workflows 4

Flexible Scheduling and Control of Bandwidth and In-transit ...

引用

Fourth international workshop on Network-Aware Data management

作者： Aktas, Mehmet Fatih Haldeman, Georgiana Parashar, Manish Rutgers State Univ Rutgers Discovery Informat Inst Piscataway NJ USA

ISBN: (纸本)9781479970193

Emerging end-to-end scientific applications that integrate high-end experiments and instruments with large scale simulations and end-user displays, require complex couplings and data sharing between distributed components involving large data volumes and varying hard (in-time data delivery) and soft (in-transit processing) quality of service (QoS) requirements. As a result, efficient data transport is a key requirement of such workflows. In this paper, we leverage software-defined networking (SDN) to address issues of data transport service control and resource provisioning to meet varying QoS requirements from multiple coupled workflows sharing the same service medium. Specifically, we present a flexible control and a disciplined resource scheduling approach for data transport services of science networks. Furthermore, we emulate an SDN testbed on top of the FutureGrid virtualized testbed and use it to evaluate our approach for a realistic scientific workflow. Our results show that SDN-based control and resource scheduling based on simple intuitive models can meet the coupling requirement with high resource utilization.

关键词： grid computing natural sciences computing quality of service resource allocation scheduling software defined networking FutureGrid virtualized testbed QoS requirements SDN bandwidth control data transport service control end-to-end application workflows end-to-end scientific applications flexible control flexible scheduling in-transit services resource provisioning resource scheduling science networks software-defined networking Bandwidth Control systems Couplings Data models Plasmas Quality of service resource management Quality of service management of resources Bandwidth bandwidth control resource utilization data models Couplings control systems Grid computing data transmission Natural sciences computing Workflow Plasmas Software defined networking

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A novel delay based application scheduling for energy efficient cloud operations

A novel delay based application scheduling for energy effici...

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international Conference on Man and Machine Interfacing (MAMI)

作者： Lenka Sri Harsha K Hemant Kumar Reddy Diptendu Sinha Roy Department of Computer Science and Engineering GITAM University Vishkapatnam India Department of Computer Science and Technology National Institute of Science and Technology Berhampur Department of Computer Science and Technology National Institute of Science and Technology Berhampur

Over the past few decades, computing environments have progressed from single-user milieu to highly parallel supercomputing environments, Network of Workstations (NoWs), distributed systems, to more recently popular systems like grids and clouds. Due to its great advantage of providing large computational capacity at low costs, cloud infrastructures can be employed as a very effective tool. However, in order to accommodate for peak computing demands, cloud service providers need to maintain huge computational infrastructure in their datacenters. Power consumption reduction in such datacenters is a major research issue. In this paper, we propose a delayed provisioning approach for applications based on certain parameters which are derived from previous logs such that the number of active servers spawned on new application requests are put under check. Simultaneously, maintaining QoS agreements with users are also taken care of. The experiments to validate the efficacy of the proposed model are carried out on a simulated environment, with varying server and user application and its parameters sizes. The simulation results presented herewith demonstrate the efficacy of the proposed approach both in terms of acceptable SLA as well as acceptable QoS.

关键词： Servers Energy consumption Cloud computing Delays Load modeling resource management Quality of service

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Integration and Evaluation of Decentralized Fairshare Prioritization (Aequus) 28

Integration and Evaluation of Decentralized Fairshare Priori...

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28th IEEE international parallel & distributed Processing Symposium workshops (IPDPSW)

作者： Espling, Daniel Ostberg, Per-Olov Elmroth, Erik Umea Univ Dept Comp Sci SE-90187 Umea Sweden

ISBN: (纸本)9781479941162

Fairshare is commonly one of the factors used by cluster resource management systems to prioritize jobs during scheduling. Despite the grid vision of a transparent and unified infrastructure, fairshare is normally calculated and enforced at the local cluster level rather than at a grid-wide scale. Aequus is a self-contained decentralized system for grid-wide fairshare job prioritization. Using Aequus, detailed global share policies can be combined with local cluster policies to offer a unified grid fairshare prioritization system where local administrations retain control over their clusters. This work shows how Aequus can be integrated with local resource management systems such as SLURM and Maui with minimal intrusion. Early results from production help assess the maturity of the system, and the system is further tested and evaluated for use at a nation-wide scale using workload modeling techniques. Statistical models are created based on historical national grid usage data, and synthetic traces based on these models are used to create a diverse input set used to exemplify system behavior. The system is shown to behave consistently despite great variations in job arrival patterns and partial participation of some of the collaborating installations.

关键词： Grid scheduling Fairshare scheduling Work-load modeling

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Proceedings of the international parallel and distributed Processing Symposium, IPDPS

Proceedings of the International Parallel and Distributed Pr...

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28th IEEE international parallel and distributed Processing Symposium workshops, IPDPSW 2014

ISBN: (纸本)9780769552088

The proceedings contain 196 papers. The topics discussed include: searching for the optimal data partitioning shape for parallel matrix matrix multiplication on 3 heterogeneous processors;taking advantage of hybrid systems for sparse direct solvers via task-based runtimes;topology-aware optimization of communications for parallel matrix multiplication on hierarchical heterogeneous HPC platform;scheduling methods for accelerating applications on architectures with heterogeneous cores;utility driven dynamic resource management in an oversubscribed energy-constrained heterogeneous system;an efficient algorithm for scheduling jobs in volunteer computing platforms;resource centered computing delivering high parallel performance;runtime behavior comparison of modern accelerators and coprocessors;and a new dataflow compiler IR for accelerating control-intensive code in spatial hardware.

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Multi resource Fairness: Problems and Challenges 1

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17th international workshop on Job scheduling Strategies for parallel Processing (JSSPP)

作者： Klusacek, Dalibor Rudova, Hana Jaros, Michal Masaryk Univ Fac Informat Bot 68a Brno Czech Republic CESNET spo Prague Czech Republic Masaryk Univ Inst Comp Sci Brno Czech Republic

ISBN: (数字)9783662437797

ISBN: (纸本)9783662437797;9783662437780

Current production resource management and scheduling systems often use some mechanism to guarantee fair sharing of computational resources among different users of the system. For example, the user who so far consumed small amount of CPU time gets higher priority and vice versa. The problem with such a solution is that it does not reflect other consumed resources like RAM, HDD storage capacity or GPU cores. Clearly, different users may have highly heterogeneous demands concerning aforementioned resources, yet they are all prioritized only with respect to consumed CPU time. In this paper we show that such a single resource-based approach is unfair and is no longer suitable for nowadays systems. We provide a survey of existing works that somehow try to deal with this situation and we closely analyze and evaluate their characteristics. Next, we propose new enhanced approaches that would allow the development of usable multi resource-aware user prioritization mechanisms. We demonstrate that different consumed resources can be weighted and combined together within a single formula which can be used to establish users' priorities. Moreover, we show that when it comes to multiple resources, it is not always possible to find a suitable solution that would fulfill all fairness-related requirements.

关键词： Multi resource fairness Fairshare Penalty scheduling

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